Download or read book Unsupervised Adaptive Signal Processing Techniques for Wireless Receivers written by Ediz Cetin and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Novel Complex Adaptive Signal Processing Techniques Employing Optimally Derived Time varying Convergence Factors with Applications in Digital Signal Processing and Wireless Communications written by Raghuram Ranganathan and published by . This book was released on 2008 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: In digital signal processing in general, and wireless communications in particular, the increased usage of complex signal representations, and spectrally efficient complex modulation schemes such as QPSK and QAM has necessitated the need for efficient and fast-converging complex digital signal processing techniques. In this research, novel complex adaptive digital signal processing techniques are presented, which derive optimal convergence factors or step sizes for adjusting the adaptive system coefficients at each iteration. In addition, the real and imaginary components of the complex signal and complex adaptive filter coefficients are treated as separate entities, and are independently updated. As a result, the developed methods efficiently utilize the degrees of freedom of the adaptive system, thereby exhibiting improved convergence characteristics, even in dynamic environments. In wireless communications, acceptable co-channel, adjacent channel, and image interference rejection is often one of the most critical requirements for a receiver. In this regard, the fixed-point complex Independent Component Analysis (ICA) algorithm, called Complex FastICA, has been previously applied to realize digital blind interference suppression in stationary or slow fading environments. However, under dynamic flat fading channel conditions frequently encountered in practice, the performance of the Complex FastICA is significantly degraded. In this dissertation, novel complex block adaptive ICA algorithms employing optimal convergence factors are presented, which exhibit superior convergence speed and accuracy in time-varying flat fading channels, as compared to the Complex FastICA algorithm. The proposed algorithms are called Complex IA-ICA, Complex OBA-ICA, and Complex CBC-ICA. For adaptive filtering applications, the Complex Least Mean Square algorithm (Complex LMS) has been widely used in both block and sequential form, due to its computational simplicity. However, the main drawback of the Complex LMS algorithm is its slow convergence and dependence on the choice of the convergence factor. In this research, novel block and sequential based algorithms for complex adaptive digital filtering are presented, which overcome the inherent limitations of the existing Complex LMS. The block adaptive algorithms are called Complex OBA-LMS and Complex OBAI-LMS, and their sequential versions are named Complex HA-LMS and Complex IA-LMS, respectively. The performance of the developed techniques is tested in various adaptive filtering applications, such as channel estimation, and adaptive beamforming. The combination of Orthogonal Frequency Division Multiplexing (OFDM) and the Multiple-Input-Multiple-Output (MIMO) technique is being increasingly employed for broadband wireless systems operating in frequency selective channels. However, MIMO-OFDM systems are extremely sensitive to Intercarrier Interference (ICI), caused by Carrier Frequency Offset (CFO) between local oscillators in the transmitter and the receiver. This results in crosstalk between the various OFDM subcarriers resulting in severe deterioration in performance. In order to mitigate this problem, the previously proposed Complex OBA-ICA algorithm is employed to recover user signals in the presence of ICI and channel induced mixing. The effectiveness of the Complex OBA-ICA method in performing ICI mitigation and signal separation is tested for various values of CFO, rate of channel variation, and Signal to Noise Ratio (SNR).

Download or read book Unsupervised Signal Processing written by João Marcos Travassos Romano and published by CRC Press. This book was released on 2018-09-03 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unsupervised Signal Processing: Channel Equalization and Source Separation provides a unified, systematic, and synthetic presentation of the theory of unsupervised signal processing. Always maintaining the focus on a signal processing-oriented approach, this book describes how the subject has evolved and assumed a wider scope that covers several topics, from well-established blind equalization and source separation methods to novel approaches based on machine learning and bio-inspired algorithms. From the foundations of statistical and adaptive signal processing, the authors explore and elaborate on emerging tools, such as machine learning-based solutions and bio-inspired methods. With a fresh take on this exciting area of study, this book: Provides a solid background on the statistical characterization of signals and systems and on linear filtering theory Emphasizes the link between supervised and unsupervised processing from the perspective of linear prediction and constrained filtering theory Addresses key issues concerning equilibrium solutions and equivalence relationships in the context of unsupervised equalization criteria Provides a systematic presentation of source separation and independent component analysis Discusses some instigating connections between the filtering problem and computational intelligence approaches. Building on more than a decade of the authors’ work at DSPCom laboratory, this book applies a fresh conceptual treatment and mathematical formalism to important existing topics. The result is perhaps the first unified presentation of unsupervised signal processing techniques—one that addresses areas including digital filters, adaptive methods, and statistical signal processing. With its remarkable synthesis of the field, this book provides a new vision to stimulate progress and contribute to the advent of more useful, efficient, and friendly intelligent systems.

Download or read book Adaptive Signal Processing written by Yiteng Huang and published by Springer Science & Business Media. This book was released on 2003-02-06 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the first time, a reference on the most relevant applications of adaptive filtering techniques. Top researchers in the field contributed chapters addressing applications in acoustics, speech, wireless and networking, where research is still very active and open.

Download or read book Adaptation in Wireless Communications Adaptive signal processing in wireless communications written by Mohamed Ibnkahla and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Complex valued Adaptive Digital Signal Enhancement for Applications in Wireless Communication Systems written by Ying Liu and published by . This book was released on 2012 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent decades, the wireless communication industry has attracted a great deal of research efforts to satisfy rigorous performance requirements and preserve high spectral efficiency. Along with this trend, I/Q modulation is frequently applied in modern wireless communications to develop high performance and high data rate systems. This has necessitated the need for applying efficient complex-valued signal processing techniques to highly-integrated, multi-standard receiver devices. In this dissertation, novel techniques for complex-valued digital signal enhancement are presented and analyzed for various applications in wireless communications. The first technique is a unified block processing approach to generate the complex-valued conjugate gradient Least Mean Square (LMS) techniques with optimal adaptations. The proposed algorithms exploit the concept of the complex conjugate gradients to find the orthogonal directions for updating the adaptive filter coefficients at each iteration. Along each orthogonal direction, the presented algorithms employ the complex Taylor series expansion to calculate time-varying convergence factors tailored for the adaptive filter coefficients. The performance of the developed technique is tested in the applications of channel estimation, channel equalization, and adaptive array beamforming. Comparing with the state of the art methods, the proposed techniques demonstrate improved performance and exhibit desirable characteristics for practical use. The second complex-valued signal processing technique is a novel Optimal Block Adaptive algorithm based on Circularity, OBA-C. The proposed OBA-C method compensates for a complex imbalanced signal by restoring its circularity. In addition, by utilizing the complex Taylor series expansion, the OBA-C method optimally updates the adaptive filter coefficients at each iteration. This algorithm can be applied to mitigate the frequency-dependent I/Q mismatch effects in analog front-end. Simulation results indicate that comparing with the existing methods, OBA-C exhibits superior convergence speed while maintaining excellent accuracy. The third technique is regarding interference rejection in communication systems. The research on both LMS and Independent Component Analysis (ICA) based techniques continues to receive significant attention in the area of interference cancellation. The performance of the LMS and ICA based approaches is studied for signals with different probabilistic distributions. Our research indicates that the ICA-based approach works better for super-Gaussian signals, while the LMS-based method is preferable for sub-Gaussian signals. Therefore, an appropriate choice of interference suppression algorithms can be made to satisfy the ever-increasing demand for better performance in modern receiver design.

Download or read book Signal Processing for Cognitive Radios written by Sudharman K. Jayaweera and published by John Wiley & Sons. This book was released on 2014-12-16 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines signal processing techniques for cognitive radios. The book is divided into three parts: Part I, is an introduction to cognitive radios and presents a history of the cognitive radio (CR), and introduce their architecture, functionalities, ideal aspects, hardware platforms, and state-of-the-art developments. Dr. Jayaweera also introduces the specific type of CR that has gained the most research attention in recent years: the CR for Dynamic Spectrum Access (DSA). Part II of the book, Theoretical Foundations, guides the reader from classical to modern theories on statistical signal processing and inference. The author addresses detection and estimation theory, power spectrum estimation, classification, adaptive algorithms (machine learning), and inference and decision processes. Applications to the signal processing, inference and learning problems encountered in cognitive radios are interspersed throughout with concrete and accessible examples. Part III of the book, Signal Processing in Radios, identifies the key signal processing, inference, and learning tasks to be performed by wideband autonomous cognitive radios. The author provides signal processing solutions to each task by relating the tasks to materials covered in Part II. Specialized chapters then discuss specific signal processing algorithms required for DSA and DSS cognitive radios.

Download or read book Adaptive Signal Processing Techniques for Robust High Capacity Spread Spectrum Multiple Access written by and published by . This book was released on 2003 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This project is concerned with signal processing and coding techniques, which can improve the performance of spread-spectrum multiple-access systems. Specific topics investigated during the course of this project include: (1) Reduced-rank interference suppression; (2) Combined coding and interference suppression, (3) Joint transmitter-receiver optimization in the presence of multiple access interference; and (4) The effect of limited feedback on the performance of joint transmitter-receiver optimization schemes. The theory of large random matrices has been used to analyze the performance of both interference suppression and interference avoidance schemes. For example, we have used these techniques to analyze the performance of adaptive reduced- and full-rank least squares filtering for interference suppression with limited training. This analysis shows the effects of algorithm parameters, which determine the initialization and data windowing, along with system load and noise level. Other contributions include optimization of the ratio of pilot-to-data power and code rate with adaptive linear interference suppression, and signature optimization for combined interference avoidance and pre-equalization of multi-path. Transmitter optimization with limited feedback has also been considered, and bounds on the achievable performance as a function of feedback bits per dimension have been obtained. This project has resulted in a patent application for an adaptive reduced-rank filter, a paper award (for work on reduced-rank filtering), and numerous journal and conference publications on the preceding topics.

Download or read book Signal Processing for Wireless Communication Systems written by H. Vincent Poor and published by Springer Science & Business Media. This book was released on 2006-01-19 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal Processing for Wireless Communication Systems brings together in one place important contributions and up-to-date research results in this fast moving area. The Contributors to this work were selected from leading researchers and practitioners in this field. The book's 18 chapters are divided into three areas: systems, Networks, and Implementation Issues; Channel Estimation and Equalization; and Multiuser Detection. The Work, originally published as Volume 30, Numbers 1-3 of the Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, will be valuable to anyone working or researching in the field of wireless communication systems. It serves as an excellent reference, providing insight into some of the most challenging issues being examined today.

Download or read book Conference Proceedings written by and published by . This book was released on 2004 with total page 738 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Adaptive Signal Processing for Energy limited Distributed Wireless Sensor Networks written by Vijay Krishna Veeramachaneni and published by . This book was released on 2004 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Handbook on Array Processing and Sensor Networks written by Simon Haykin and published by John Wiley & Sons. This book was released on 2010-02-12 with total page 924 pages. Available in PDF, EPUB and Kindle. Book excerpt: A handbook on recent advancements and the state of the art in array processing and sensor Networks Handbook on Array Processing and Sensor Networks provides readers with a collection of tutorial articles contributed by world-renowned experts on recent advancements and the state of the art in array processing and sensor networks. Focusing on fundamental principles as well as applications, the handbook provides exhaustive coverage of: wavelets; spatial spectrum estimation; MIMO radio propagation; robustness issues in sensor array processing; wireless communications and sensing in multi-path environments using multi-antenna transceivers; implicit training and array processing for digital communications systems; unitary design of radar waveform diversity sets; acoustic array processing for speech enhancement; acoustic beamforming for hearing aid applications; undetermined blind source separation using acoustic arrays; array processing in astronomy; digital 3D/4D ultrasound imaging technology; self-localization of sensor networks; multi-target tracking and classification in collaborative sensor networks via sequential Monte Carlo; energy-efficient decentralized estimation; sensor data fusion with application to multi-target tracking; distributed algorithms in sensor networks; cooperative communications; distributed source coding; network coding for sensor networks; information-theoretic studies of wireless networks; distributed adaptive learning mechanisms; routing for statistical inference in sensor networks; spectrum estimation in cognitive radios; nonparametric techniques for pedestrian tracking in wireless local area networks; signal processing and networking via the theory of global games; biochemical transport modeling, estimation, and detection in realistic environments; and security and privacy for sensor networks. Handbook on Array Processing and Sensor Networks is the first book of its kind and will appeal to researchers, professors, and graduate students in array processing, sensor networks, advanced signal processing, and networking.

Download or read book Adaptive Narrow band Interface Rejection in a Ds spread Spectrum Intercept Receiver Using Transform Domain Signal Processing Techniques written by John M. Gevargiz and published by . This book was released on 1987 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Signal Processing in Wireless Communications written by Adam C. Polak and published by . This book was released on 2014 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid progress of wireless communication technologies that has taken place in recent years has significantly improved the quality of everyday life. However with this expansion of wireless communication systems come significant security threats and significant technological challenges, both of which are due to the fact that the communication medium is shared. The ubiquity of open wireless Internet access networks creates a new avenue for cyber-criminals to impersonate and act in an unauthorized way. The increasing number of deployed wide-band wireless communication systems entails technological challenges for effective utilization of the shared medium, which implies the need for advanced interference rejection methods. Wireless security and interference rejection in wide-band wireless communications are therefore often considered as the two main challenges in wireless network's design and research. Important aspects of these challenges are illuminated and addressed in this dissertation. This dissertation considers signal processing approaches for exploiting or mitigating the effects of non-ideal components in wireless communication systems. In the first part of the dissertation, we introduce and study a novel, model-based approach to wireless device identification that exploits imperfections in the transmitter caused by manufacturing process nonidealities. Previous approaches to device identification based on hardware imperfections vary from transient analysis to machine learning but have not provided verifiable accuracy. Here, we detail a model-based approach, that uses statistical models of RF transmitter components: digital-to-analog converter, power amplifier and RF oscillator, which are amenable for analysis. Our proposed approach examines the key device characteristics that cause anonymity loss, countermeasures that can be applied by the nodes to regain the anonymity, and ways of thwarting such countermeasures. We develop identification algorithms based on statistical signal processing methods and address the challenging scenario when the units that need to be distinguished from one another are of the same model and from the same manufacturer. Using simulations and measurements of components that are commonly used in commercial communications systems, we show that our anonymity breaking techniques are effective. In the second part of the dissertation, we consider innovative approaches for the acquisition of frequency-sparse signals with wide-band receivers when a weak signal of interest is received in the presence of a very strong interference, and the effects of the nonlinearities in the low-noise amplifier at the receiver must be mitigated. All samples with amplitude above a given threshold, dictated by the linear input range of the receiver, are discarded to avoid the distortion caused by saturation of the low noise amplifier. Such a sampling scheme, while avoiding nonlinear distortion that cannot be corrected in the digital domain, poses challenges for signal reconstruction techniques, as the samples are taken non-uniformly, but also non-randomly. The considered approaches fall into the field of compressive sensing (CS); however, what differentiates them from conventional CS is that a structure is forced upon the measurement scheme. Such a structure causes a violation of the core CS assumption of the measurements' randomness. We consider two different types of structured acquisition: signal independent and signal dependent structured acquisition. For the first case, we derive bounds on the number of samples needed for successful CS recovery when samples are drawn at random in predefined groups. For the second case, we consider enhancements of CS recovery methods when only small-amplitude samples of the signal that needs to be recovered are available for the recovery. Finally, we address a problem of spectral leakage due to the limited processing block size of block processing, wide-band receivers and propose an adaptive block size adjustment method, which leads to significant dynamic range improvements.

Download or read book Adaptive Antennas for Wireless Communications written by George V. Tsoulos and published by Wiley-IEEE Press. This book was released on 2001-01-15 with total page 790 pages. Available in PDF, EPUB and Kindle. Book excerpt: Electrical Engineering Adaptive Antennas for Wireless Communications In the past decade, the wireless communications community recognized adaptive antennas as a core technology that would help existing systems overcome problems related to spectrum efficiency and provide a vehicle to achieve the ambitious requirements of next-generation networks. The communications industry has already begun to develop adaptive antenna systems for commercial use and at the same time is working with standardization institutes around the world to produce adaptive antenna-friendly standards. Adaptive Antennas for Wireless Communications is a concise, detailed resource of information for all critical issues related to this technology and is compiled from the original published work of experts in the field. The extensive literature covers: * Historical and background aspects * Radio channel simulation techniques and characteristics * Adaptive algorithm performance under a variety of conditions * Adaptive antenna performance in different operational environments * Design and implementation issues * Experimental results * Other issues such as network planning and recent novel techniques Adaptive Antennas for Wireless Communications is a valuable reference for helping consultants, researchers, communications professionals, academics, and students gain an in-depth understanding of adaptive antenna technology.

Download or read book Digital Matching of Receivers for an Adaptive antenna Receiving System written by and published by . This book was released on 1997 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mismatch of receivers in an adaptive antenna receiving system can limit the interference suppression performance. The precision of matching is critical in cases where the unwanted interference signals to be suppressed are much stronger than the desired signal. This paper describes a simple calibration technique for suppression of very strong interference signals using a digital signal processing technique. The proposed scheme uses a sequence of stepped tones scanning across the receiver bandwidth. An example is provided to illustrate the procedure.

Download or read book Adaptive Signal Combining and Detection in Cooperative Wireless Networks written by Athar Qureshi and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this research adaptive algorithms were developed for multiuser detection and signal combining in cooperative wireless networks. Some of the key contributions and works of this research thesis are: 1. A computationally simple Adaptive Minimum Mean Square Error Multiuser Detection scheme was proposed to eliminate multiple access interference in uplink communication of an asynchronous cooperative CDMA wireless network, where users cooperate in a relaying mode while they exchange data and channel information with the destination node. The proposed scheme provides better interference resistance than optimum multiuser detection Maximum Likelihood Sequence Estimation in cooperative wireless networks. The performance was examined under Amplify-and-Forward and Decode-and-Forward cooperative protocols in flat fading Rayleigh wireless channels. 2. Adaptive signal combining was proposed for cooperative wireless networks and its performance was analysed by using Least Mean Square and Recursive Least Square algorithms. The other classical non-adaptive techniques Maximal Ratio Combining and Wiener were also examined. It was also shown that adaptive signal combining achieves Wiener's solution in cooperative wireless networks with added benefit of computational simplicity over classical combining schemes. 3. Weighted Least Square Error Method of signal combining was proposed for wireless signal combining, where estimates of inverse of the channel noise variance was used as weight of the combiner. The proposed method was a receiver with noise estimation filters at each received branch for the noise estimation. The reciprocal of the estimate of the channels noise variance were used as weights of combiner to achieve Wiener's solution of signal combining. The proposed algorithm was used in cooperative, non cooperative wireless networks and multiple antennas system. It was also shown that un weighted least square error method is equivalent to equal gain combining scheme. The performance of the proposed mathematical algorithms were examined with computer simulations in various wireless channel models.