Algorithms for Blind Equalization Based on Relative Gradient and Toeplitz Constraints

Blind Equalization (BE) refers to the problem of recovering the source symbol sequence from a signal received through a channel in the presence of additive noise and channel distortion, when the channel response is unknown and a training sequence is not accessible. To achieve BE, statistical or constellation properties of the source symbols are exploited. In BE algorithms, two main concerns are convergence speed and computational complexity. In this dissertation, we explore the application of relative gradient for equalizer adaptation with a structure constraint on the equalizer matrix, for fast convergence without excessive computational complexity. We model blind equalization with symbol-rate sampling as a blind source separation (BSS) problem and study two single-carrier transmission schemes, specifically block transmission with guard intervals and continuous transmission. Under either scheme, blind equalization can be achieved using independent component analysis (ICA) algorithms with a Toeplitz or circulant constraint on the structure of the separating matrix. We also develop relative gradient versions of the widely used Bussgang-type algorithms. Processing the equalizer outputs in sliding blocks, we are able to use the relative gradient for adaptation of the Toeplitz constrained equalizer matrix. The use of relative gradient makes the Bussgang condition appear explicitly in the matrix adaptation and speeds up convergence. For the ICA-based and Bussgang-type algorithms with relative gradient and matrix structure constraints, we simplify the matrix adaptations to obtain equivalent equalizer vector adaptations for reduced computational cost. Efficient implementations with fast Fourier transform, and approximation schemes for the cross-correlation terms used in the adaptation, are shown to further reduce computational cost. We also consider the use of a relative gradient algorithm for channel shortening in orthogonal frequency division multiplexing (OFDM) systems. The redundancy of the cyclic prefix symbols is used to shorten a channel with a long impulse response. We show interesting preliminary results for a shortening algorithm based on relative gradient

Digital Signal Processing on FPGA for Short-Range Optical Communications Systems over Plastic Optical Fiber

Nowadays bandwidth requirements are increasing vertiginously. As new ways and concepts of how to share information emerge, new ways of how to access the web enter the market. Computers and mobile devices are only the beginning, the spectrum of web products and services such as IPTV, VoIP, on-line gaming, etc has been augmented by the possibility to share, store data, interact and work on the Cloud. The rush for bandwidth has led researchers from all over the world to enquire themselves on how to achieve higher data rates, and it is thanks to their efforts, that both long-haul and short-range communications systems have experienced a huge development during the last few years. However, as the demand for higher information throughput increases traditional short-range solutions reach their lim- its. As a result, optical solutions are now migrating from long-haul to short-range communication systems. As part of this trend, plastic optical fiber (POF) systems have arisen as promising candidates for applications where traditional glass optical fibers (GOF) are unsuitable. POF systems feature a series of characteristics that make them very suitable for the market requirements. More in detail, these systems are low cost, robust, easy to handle and to install, flexible and yet tolerant to bendings. Nonetheless, these features come at the expense of a considerable higher bandwidth limitation when compared to GOF systems. This thesis is aimed to the investigate the use of digital signal processing (DSP) algorithms to overcome the bandwidth limitation in short-range optical communications system based on POF. In particular, this dissertation presents the design and development of DSP algorithms on field programmable gate arrays (FPGAs) with the ultimate purpose of implementing a fully engineered 1Gbit/s Ethernet Media Converter capable of establishing data links over 50+ meters of PMMA-SI POF using an RC-LED as transmitte

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

An investigation into the performance of a power-of-two coefficient transversal equalizer in a 34Mbit/s QPSK digital radio during frequency-selective fading conditions

Bibliography: leaves 82-91.Under certain atmospheric conditions, multipath propagation can occur. The interaction of radio waves arriving at a receiver, having travelled via paths of differing length, results in the phenomenon of frequency-selective fading. This phenomenon manifests as a notch in the received spectrum and causes a severe degradation in the performance of a digital radio system. As the total power in the received bandwidth may be unaffected, the Automatic Gain Control is not able to correct for this distortion, and so other methods are required. The dissertation commences with a summary of the phenomenon of multipath as this provides the context for the investigations which follow. The adaptive equalizer was developed to combat the distortion introduced by frequency-selective fading. It achieves this by applying an estimate of the inverse of the distorting channel's transfer function. The theory on adaptive equalizers has been well established, and a summary of this theory is presented in the form of Wiener Filter theory and the Wiener-Hopf equations. An adaptive equalizer located in a 34MBit/s QPSK digital radio is required to operate at very high speed, and its digital hardware implementation is not a trivial task. In order to reduce the cost and complexity, a compromise was proposed. If the tap weights of the equalizer could be represented by power-of-two binary numbers, the equalizer circuitry can be dramatically simplified. The aim of the dissertation was to investigate the performance of this simplified equalizer structure and to determine whether a power-of-two equalizer was a viable consideration

Advanced automatic mixing tools for music

PhDThis thesis presents research on several independent systems that when combined together can generate an automatic sound mix out of an unknown set of multi‐channel inputs. The research explores the possibility of reproducing the mixing decisions of a skilled audio engineer with minimal or no human interaction. The research is restricted to non‐time varying mixes for large room acoustics. This research has applications in dynamic sound music concerts, remote mixing, recording and postproduction as well as live mixing for interactive scenes. Currently, automated mixers are capable of saving a set of static mix scenes that can be loaded for later use, but they lack the ability to adapt to a different room or to a different set of inputs. In other words, they lack the ability to automatically make mixing decisions. The automatic mixer research depicted here distinguishes between the engineering mixing and the subjective mixing contributions. This research aims to automate the technical tasks related to audio mixing while freeing the audio engineer to perform the fine‐tuning involved in generating an aesthetically‐pleasing sound mix. Although the system mainly deals with the technical constraints involved in generating an audio mix, the developed system takes advantage of common practices performed by sound engineers whenever possible. The system also makes use of inter‐dependent channel information for controlling signal processing tasks while aiming to maintain system stability at all times. A working implementation of the system is described and subjective evaluation between a human mix and the automatic mix is used to measure the success of the automatic mixing tools

Optics for AI and AI for Optics

Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields

Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications