In Car Audio

This chapter presents implementations of advanced in Car Audio Applications. The system is composed by three main different applications regarding the In Car listening and communication experience. Starting from a high level description of the algorithms, several implementations on different levels of hardware abstraction are presented, along with empirical results on both the design process undergone and the performance results achieved

FPGA implementations for parallel multidimensional filtering algorithms

PhD ThesisOne and multi dimensional raw data collections introduce noise and artifacts, which need to be recovered from degradations by an automated filtering system before, further machine analysis. The need for automating wide-ranged filtering applications necessitates the design of generic filtering architectures, together with the development of multidimensional and extensive convolution operators. Consequently, the aim of this thesis is to investigate the problem of automated construction of a generic parallel filtering system. Serving this goal, performance-efficient FPGA implementation architectures are developed to realize parallel one/multi-dimensional filtering algorithms. The proposed generic architectures provide a mechanism for fast FPGA prototyping of high performance computations to obtain efficiently implemented performance indices of area, speed, dynamic power, throughput and computation rates, as a complete package. These parallel filtering algorithms and their automated generic architectures tackle the major bottlenecks and limitations of existing multiprocessor systems in wordlength, input data segmentation, boundary conditions as well as inter-processor communications, in order to support high data throughput real-time applications of low-power architectures using a Xilinx Virtex-6 FPGA board. For one-dimensional raw signal filtering case, mathematical model and architectural development of the generalized parallel 1-D filtering algorithms are presented using the 1-D block filtering method. Five generic architectures are implemented on a Virtex-6 ML605 board, evaluated and compared. A complete set of results on area, speed, power, throughput and computation rates are obtained and discussed as performance indices for the 1-D convolution architectures. A successful application of parallel 1-D cross-correlation is demonstrated. For two dimensional greyscale/colour image processing cases, new parallel 2-D/3-D filtering algorithms are presented and mathematically modelled using input decimation and output image reconstruction by interpolation. Ten generic architectures are implemented on the Virtex-6 ML605 board, evaluated and compared. Key results on area, speed, power, throughput and computation rate are obtained and discussed as performance indices for the 2-D convolution architectures. 2-D image reconfigurable processors are developed and implemented using single, dual and quad MAC FIR units. 3-D Colour image processors are devised to act as 3-D colour filtering engines. A 2-D cross-correlator parallel engine is successfully developed as a parallel 2-D matched filtering algorithm for locating any MRI slice within a MRI data stack library. Twelve 3-D MRI filtering operators are plugged in and adapted to be suitable for biomedical imaging, including 3-D edge operators and 3-D noise smoothing operators. Since three dimensional greyscale/colour volumetric image applications are computationally intensive, a new parallel 3-D/4-D filtering algorithm is presented and mathematically modelled using volumetric data image segmentation by decimation and output reconstruction by interpolation, after simultaneously and independently performing 3-D filtering. Eight generic architectures are developed and implemented on the Virtex-6 board, including 3-D spatial and FFT convolution architectures. Fourteen 3-D MRI filtering operators are plugged and adapted for this particular biomedical imaging application, including 3-D edge operators and 3-D noise smoothing operators. Three successful applications are presented in 4-D colour MRI (fMRI) filtering processors, k-space MRI volume data filter and 3-D cross-correlator.IRAQI Government

Reduced-complexity Digital Predistortion in Flexible Radio Spectrum Access

Wireless communications is nowadays seen as one of the main foundations of technological advancements in, e.g., healthcare, education, agriculture, transportation, computing, personal communications, media, and entertainment. This requires major technological developments and advances at different levels of the wireless communication systems and networks. In particular, it is required to utilize the currently available frequency spectrum in a more and more efficient way, while also adopting new spectral bands. Moreover, it is required that cheaper and smaller electronic components are used to build future wireless communication systems to facilitate increasingly cost-effective solutions. Meanwhile, energy efficiency becomes extremely important in wide scale deployments of the networks both from a running cost point of view, and from an environmental impact point of view. This is the big picture, or the so called ‘bird’s eye view’ of the challenges that are yet to be met in this very interesting and fast developing field of science.The power amplifier (PA) is the most power-hungry component in most RF transmitters. Consequently, its energy efficiency significantly contributes to the overall energy efficiency of the transmitter, and in fact the whole wireless network. Unfortunately, energy efficiency enhancement implies operating the PA closer to its saturation region, which typically results in severe nonlinear distortion that can deteriorate the signal quality and cause interference to neighboring users, both of which negatively impact the system spectral efficiency. Moreover, in flexible spectrum access scenarios, which are essential for improving the spectral efficiency, particular in the form of non-contiguous radio spectrum access, the nonlinear distortion due to the PA becomes even more severe and can significantly impact the overall network performance. For example, in noncontiguous carrier aggregation (CA) in LTE-Advanced, it has been demonstrated that in addition to the classical in-band distortion and regrowth around the main carriers, harmful spurious emission components are generated which can easily violate the spurious emission limits even in the case of user equipment (UE) transmitters.Technological advances in the digital electronics domain have enabled us to approach this problem from a digital signal processing point of view in the form of widely-adopted and researched digital predistortion (DPD) technology. However, when the signal bandwidth gets larger, and flexible or non-contiguous spectrum access is introduced, the complexity of the DPD increases and the power consumed in the digital domain by the DPD itself becomes higher and higher, to the extent that it might be close to, or even surpass, the energy savings achieved from using a more efficient PA. The problem becomes even more challenging at the UE side which has relatively limited computational capabilities and lower transmit power. This dilemma can be resolved by developing novel reduced-complexity DPD solutions in such flexible spectrum access and/or wide bandwidth scenarios while not sacrificing the DPD performance, which is the main topic area that this thesis work contributes to.The first contribution of this thesis is the development of a spur-injection based sub-band DPD structure for spurious emission mitigation in noncontiguous transmission scenarios. A novel and effective learning algorithm is also introduced, for the proposed sub-band DPD, based on the decorrelation principle. Mathematical models of the unwanted emissions are formulated based on realistic PA models with memory, followed by developing an efficient DPD structure for mitigating these emissions with reducedcomplexity in both the DPD main processing and learning paths while providing excellent spurious emission suppression. In the special case when the spurious emissions overlap with the own RX band in frequency division duplexing (FDD) transceivers, a novel subband DPD solution is also developed that uses the main RX for DPD learning without requiring any additional observation RX, thus further reducing the DPD complexity.The second contribution is the development of a novel reduced-complexity concurrent DPD, with a single-feedback receiver path, for carrier aggregation-like scenarios. The proposed solution is based on a simple and flexible DPD structure with decorrelationbased parameter learning. Practical simulations and RF measurements demonstrate that the proposed concurrent DPD provides excellent linearization performance, in terms of in-band error vector magnitude (EVM) and adjacent channel leakage ratio (ACLR), when compared to state-of-the-art concurrent DPD solutions, despite its reduced computational complexity in both the DPD main path processing and parameter learning.The third contribution is the development of a new and novel frequency-optimized DPD solution which can tailor its linearization capabilities to any particular regions of the spectrum. Detailed mathematical expressions of the power spectrum at the PA output as a function of the DPD coefficients are formulated. A Newton-Raphson optimization routine is then utilized to optimize the suppression of unwanted emissions at arbitrary pre-specified frequencies at the PA output. From a complexity reduction perspective, this means that for a given linearization performance at a particular frequency range, an optimized and reduced-complexity DPD can be used.Detailed quantitative complexity analysis, of all the proposed DPD solutions, is performed in this thesis. The complexity and linearization performance are also compared to state-of-the-art DPD solutions in the literature to validate and demonstrate the complexity reduction aspect without sacrificing the linearization performance. Moreover, all the DPD solutions developed in this thesis are tested in practical RF environments using real cellular power amplifiers that are commercially used in the latest wireless communication systems, both at the base station side and at the mobile terminal side. These experiments, along with the strong theoretical foundation of the developed DPD solutions prove that they can be commercially used as such to enhance the performance, energy efficiency, and cost effectiveness of next generation wireless transmitters

Digital Microphone Array - Design, Implementation and Speech Recognition Experiments

The instrumented meeting room of the future will help meetings to be more efficient and productive. One of the basic components of the instrumented meeting room is the speech recording device, in most cases a microphone array. The two basic requirements for this microphone array are portability and cost-efficiency, neither of which are provided by current commercially available arrays. This will change in the near future thanks to the availability of new digital MEMS microphones. This dissertation reports on the first successful implementation of a digital MEMS microphone array. This digital MEMS microphone array was designed, implemented, tested and evaluated and successfully compared with an existing analogue microphone array using a state-of-the-art ASR system and adaptation algorithms. The newly built digital MEMS microphone array compares well with the analogue microphone array on the basis of the word error rate achieved in an automated speech recognition system and is highly portable and economical

The low bit-rate coding of speech signals

Imperial Users onl

Ultra Wideband

Ultra wideband (UWB) has advanced and merged as a technology, and many more people are aware of the potential for this exciting technology. The current UWB field is changing rapidly with new techniques and ideas where several issues are involved in developing the systems. Among UWB system design, the UWB RF transceiver and UWB antenna are the key components. Recently, a considerable amount of researches has been devoted to the development of the UWB RF transceiver and antenna for its enabling high data transmission rates and low power consumption. Our book attempts to present current and emerging trends in-research and development of UWB systems as well as future expectations

Linear Operation of Switch-Mode Outphasing Power Amplifiers

Radio transceivers are playing an increasingly important role in modern society. The ”connected” lifestyle has been enabled by modern wireless communications. The demand that has been placed on current wireless and cellular infrastructure requires increased spectral efficiency however this has come at the cost of power efficiency. This work investigates methods of improving wireless transceiver efficiency by enabling more efficient power amplifier architectures, specifically examining the role of switch-mode power amplifiers in macro cell scenarios. Our research focuses on the mechanisms within outphasing power amplifiers which prevent linear amplification. From the analysis it was clear that high power non-linear effects are correctable with currently available techniques however non-linear effects around the zero crossing point are not. As a result signal processing techniques for suppressing and avoiding non-linear operation in low power regions are explored. A novel method of digital pre-distortion is presented, and conventional techniques for linearisation are adapted for the particular needs of the outphasing power amplifier. More unconventional signal processing techniques are presented to aid linearisation of the outphasing power amplifier, both zero crossing and bandwidth expansion reduction methods are designed to avoid operation in nonlinear regions of the amplifiers. In combination with digital pre-distortion the techniques will improve linearisation efforts on outphasing systems with dynamic range and bandwidth constraints respectively. Our collaboration with NXP provided access to a digital outphasing power amplifier, enabling empirical analysis of non-linear behaviour and comparative analysis of behavioural modelling and linearisation efforts. The collaboration resulted in a bench mark for linear wideband operation of a digital outphasing power amplifier. The complimentary linearisation techniques, bandwidth expansion reduction and zero crossing reduction have been evaluated in both simulated and practical outphasing test benches. Initial results are promising and indicate that the benefits they provide are not limited to the outphasing amplifier architecture alone. Overall this thesis presents innovative analysis of the distortion mechanisms of the outphasing power amplifier, highlighting the sensitivity of the system to environmental effects. Practical and novel linearisation techniques are presented, with a focus on enabling wide band operation for modern communications standards

Applications of MATLAB in Science and Engineering

The book consists of 24 chapters illustrating a wide range of areas where MATLAB tools are applied. These areas include mathematics, physics, chemistry and chemical engineering, mechanical engineering, biological (molecular biology) and medical sciences, communication and control systems, digital signal, image and video processing, system modeling and simulation. Many interesting problems have been included throughout the book, and its contents will be beneficial for students and professionals in wide areas of interest

Enhancement and optimization of a multi-command-based brain-computer interface

Brain-computer interfaces (BCI) assist disabled person to control many appliances without any physically interaction (e.g., pressing a button). SSVEP is brain activities elicited by evoked signals that are observed by visual stimuli paradigm. In this dissertation were addressed the problems which are oblige more usability of BCI-system by optimizing and enhancing the performance using particular design. Main contribution of this work is improving brain reaction response depending on focal approaches