Active Noise Control of a Forest Machine Cabin
Today, a high noise level is considered a problem in many working environments. The main reason is that it contributes to stress and fatigue. Traditional methods using passive noise control is only practicable for high frequencies. As a complement to passive noise control, active noise control (ANC) can be used to reduce low frequency noise. The main idea of ANC is to use destructive interference of waves to cancel disturbing noises. The purpose of this thesis is to design and implement an ANC system in the driver's cabin of a Valmet 890 forest machine. The engine boom is one of the most disturbing noises and therefore the main subjective for the ANC system to suppress. The ANC system is implemented on a Texas Instrument DSP development starter kit. Different FxLMS algorithms are evaluated with feedback and feedforward configurations. The results indicate that an ANC system significantly reduces the sound pressure level (SPL) in the cabin. Best performance of the evaluated systems is achieved for the feedforward FxLMS system. For a commonly used engine speed of 1500 rpm, the SPL is reduced with 17 dB. The results show fast enough convergence and global suppression of low frequency noise.
Algorithms and tools for automatic generation of DSP hardware structures
The increased complexity of Digital Signal Processing (DSP) algorithms demands for the development of more complex and more efficient hardware structures. The work presented herein describes the core components for the development of a tool capable of automatic generation of efficient hardware structures, therefore facilitating developers work. It comprises algorithms and techniques for i) balancing the paths in a graph, ii) scheduling of operations to functional units, iii) allocating registers and iv) generating the VHDL code. Results show that the developed techniques are capable of generating the hardware structure of typical DSP algorithms represented in data-flow graphs with over 2,000 nodes in around 200 ms, scaling to 80,000 nodes in about 214 s. Within the developed techniques, solving the scheduling problem is one of the most complex tasks: it is a NP-complete problem and directly influences the number of functional units and registers required. Therefore, experimental analysis was made on scheduling algorithms for time-constrained problems. Results show that simple list-based algorithms are more efficient in large problems than more complex algorithms: they run faster and tend to require less functional units.
DSP Platform Benchmarking
Benchmarking of DSP kernel algorithms was conducted in the thesis on a DSP processor for teaching in the course TESA26 in the department of Electrical Engineering. It includes benchmarking on cycle count and memory usage. The goal of the thesis is to evaluate the quality of a single MAC DSP instruction set and provide suggestions for further improvement in instruction set architecture accordingly. The scope of the thesis is limited to benchmark the processor only based on assembly coding. The quality check of compiler is not included. The method of the benchmarking was proposed by BDTI, Berkeley Design Technology Incorporations, which is the general methodology used in world wide DSP industry. Proposals on assembly instruction set improvements include the enhancement of FFT and DCT. The cycle cost of the new FFT benchmark based on the proposal was XX% lower, showing that the proposal was right and qualified. Results also show that the proposal promotes the cycle cost score for matrix computing, especially matrix multiplication. The benchmark results were compared with general scores of single MAC DSP processors offered by BDTI.
Digital Signal Processing Maths
Modern digital signal processing makes use of a variety of mathematical techniques. These techniques are used to design and understand efficient filters for data processing and control.
Wavelet Denoising for TDR Dynamic Range Improvement
A technique is presented for removing large amounts of noise present in time-domain-reflectometry (TDR) waveforms to increase the dynamic range of TDR waveforms and TDR based s-parameter measurements.
IMPLEMENTATION OF PERIODOGRAM SMOOTHING OF NOISYIMPLEMENTATION OF PERIODOGRAM SMOOTHING OF NOISY SIGNALS USING TMS320C6713 DSK
Periodogram Smoothing is a technique of power spectrum estimation. The discrete Fourier transform of a digital signal simply resolves the frequency components. The algorithm is implemented on Texas Instruments’ TMS320C6713 DSP Starter Kit (DSK). This is a 32-bit floating-point digital signal processor running at 225 MHz. The programs are basically written in the C programming language. However, those sections of code which are time-critical and memory-critical are written in assembly language of C6713. A MATLAB™ graphical user interface is also provided. The MATLAB™ program calls C programs loaded in Code Composer Studio (CCS). The C programs in turn call the assembly programs when required.
Optimization of Audio Processing algorithms (Reverb) on ARMv6 family of processors
Audio processing algorithms are increasingly used in cell phones and today’s customers are placing more demands on cell phones. Feature phones, once the advent of mobile phone technology, nowadays do more than just providing the user with MP3 play back or advanced audio effects. These features have become an integral part of medium as well as low-end phones. On the other hand, there is also an endeavor to include as improved quality as possible into products to compete in market and satisfy users’ needs. Tackling the above requirements has been partly satisfied by the advance in hardware design and manufacturing technology. However, as new hardware emerges into market the need for competence to write efficient software and exploit the new features thoroughly and effectively arises. Even though compilers are also keeping up with the new tide space for hand optimized code still exist. Wrapped in the above goal, an effort was made in this thesis to partly cover the competence requirement at Multimedia Section (part of Ericsson Mobile Platforms) to develope optimized code for new processors. Forging persistently ahead with new products, EMP has always incorporated the latest technology into its products among which ARMv6 family of processors has the main central processing role in a number of upcoming products. To fully exploit latest features provided by ARMv6, it was required to probe its new instruction set among which new media processing instructions are of outmost importance. In order to execute DSP-intensive algorithms (e.g. Audio Processing algorithms) efficiently, the implementation should be done in low-level code applying available instruction set. Meanwhile, ARMv6 comes with a number of new features in comparison with its predecessors. SIMD (Single Instruction Multiple Data) and VFP (Vector Floating Point) are the most prominent media processing improvements in ARMv6. Aligned with thesis goals and guidelines, Reverb algorithm which is among one of the most complicated audio features on a hand-held devices was probed. Consequently, its kernel parts were identified and implementation was done both in fixed-point and floating-point using the available resources on hardware. Besides execution time and amount of code memory for each part were measured and provided in tables and charts for comparison purposes. Conclusions were finally drawn based on developed code’s efficiency over ARM compiler’s as well as existing code already developed and tailored to ARMv5 processors. The main criteria for optimization was the execution time. Moreover, quantization effect due to limited precision fixed-point arithmetic was formulated and its effect on quality was elaborated. The outcomes, clearly indicate that hand optimization of kernel parts are superior to Compiler optimized alternative both from the point of code memory as well as execution time. The results also confirmed the presumption that hand optimized code using new instruction set can improve efficiency by an average 25%-50% depending on the algorithm structure and its interaction with other parts of audio effect. Despite its many draw backs, fixed-point implementation remains yet to be the dominant implementation for majority of DSP algorithms on low-power devices.
Algorithm Adaptation and Optimization of a Novel DSP Vector Co-processor
The Division of Computer Engineering at Linköping's university is currently researching the possibility to create a highly parallel DSP platform, that can keep up with the computational needs of upcoming standards for various applications, at low cost and low power consumption. The architecture is called ePUMA and it combines a general RISC DSP master processor with eight SIMD co-processors on a single chip. The master processor will act as the main processor for general tasks and execution control, while the co-processors will accelerate computing intensive and parallel DSP kernels.This thesis investigates the performance potential of the co-processors by implementing matrix algebra kernels for QR decomposition, LU decomposition, matrix determinant and matrix inverse, that run on a single co-processor. The kernels will then be evaluated to find possible problems with the co-processors' microarchitecture and suggest solutions to the problems that might exist. The evaluation shows that the performance potential is very good, but a few problems have been identified, that causes significant overhead in the kernels. Pipeline mismatches, that occurs due to different pipeline lengths for different instructions, causes pipeline hazards and the current solution to this, doesn't allow effective use of the pipeline. In some cases, the single port memories will cause bottlenecks, but the thesis suggests that the situation could be greatly improved by using buffered memory write-back. Also, the lack of register forwarding makes kernels with many data dependencies run unnecessarily slow.
Automated Accident Detection in Intersections Via Digital Audio Signal Processing
The aim of this thesis is to design a system for automated accident detection in intersections. The input to the system is a three-second audio signal. The system can be operated in two modes: two-class and multi-class. The output of the two-class system is a label of “crash” or “non-crash”. In the multi-class system, the output is the label of “crash” or various non-crash incidents including “pile drive”, “brake”, and “normal-traffic” sounds. The system designed has three main steps in processing the input audio signal. They are: feature extraction, feature optimization and classification. Five different methods of feature extraction are investigated and compared; they are based on the discrete wavelet transform, fast Fourier transform, discrete cosine transform, real cepstrum transform and Mel frequency cepstral transform. Linear discriminant analysis (LDA) is used to optimize the features obtained in the feature extraction stage by linearly combining the features using different weights. Three types of statistical classifiers are investigated and compared: the nearest neighbor, nearest mean, and maximum likelihood methods. Data collected from Jackson, MS and Starkville, MS and the crash signals obtained from Texas Transportation Institute crash test facility are used to train and test the designed system. The results showed that the wavelet based feature extraction method with LDA and maximum likelihood classifier is the optimum design. This wavelet-based system is computationally inexpensive compared to other methods. The system produced classification accuracies of 95% to 100% when the input signal has a signal-to-noise-ratio of at least 0 decibels. These results show that the system is capable of effectively classifying “crash” or “non-crash” on a given input audio signal.
Benchmarking a DSP processor
This Master thesis describes the benchmarking of a DSP processor. Benchmarking means measuring the performance in some way. In this report, we have focused on the number of instruction cycles needed to execute certain algorithms. The algorithms we have used in the benchmark are all very common in signal processing today. The results we have reached in this thesis have been compared to benchmarks for other processors, performed by Berkeley Design Technology, Inc. The algorithms were programmed in assembly code and then executed on the instruction set simulator. After that, we proposed changes to the instruction set, with the aim to reduce the execution time for the algorithms. The results from the benchmark show that our processor is at the same level as the ones tested by BDTI. Probably would a more experienced programmer be able to reduce the cycle count even more, especially for some of the more complex benchmarks.
Benchmarking a DSP processor
This Master thesis describes the benchmarking of a DSP processor. Benchmarking means measuring the performance in some way. In this report, we have focused on the number of instruction cycles needed to execute certain algorithms. The algorithms we have used in the benchmark are all very common in signal processing today. The results we have reached in this thesis have been compared to benchmarks for other processors, performed by Berkeley Design Technology, Inc. The algorithms were programmed in assembly code and then executed on the instruction set simulator. After that, we proposed changes to the instruction set, with the aim to reduce the execution time for the algorithms. The results from the benchmark show that our processor is at the same level as the ones tested by BDTI. Probably would a more experienced programmer be able to reduce the cycle count even more, especially for some of the more complex benchmarks.
Correlation and Power Spectrum
In the signals and systems course and in the first course in digital signal processing, a signal is, most often, characterized by its amplitude spectrum in the frequency-domain and its amplitude profile in the time-domain. So much a student gets used to this type of characterization, that the student finds it difficult to appreciate, when encountered in the ensuing statistical signal processing course, the fact that a signal can also be characterized by its autocorrelation function in the time-domain and the corresponding power spectrum in the frequency-domain and that the amplitude characterization is not available. In this article, the characterization of a signal by its autocorrelation function in the time-domain and the corresponding power spectrum in the frequency-domain is described. Cross-correlation of two signals is also presented.
Digital Signal Processing Maths
Modern digital signal processing makes use of a variety of mathematical techniques. These techniques are used to design and understand efficient filters for data processing and control.
DSP Memory Management in a Third Generation High Performance Base Station
Most of the tasks in a mobile cellular network base station are performed with programmable digital signal processors. Their memory spaces and management features are very limited. The buffering requirements in the base station can have large instantaneous variations during the simultaneous transmission of burst' data on multiple channels to multiple users. In particular the high bit-rates of the Wideband Code Division Multiple Access data transfer evolution High Speed Downlink Packet Access create very high demands for buffering. The fragmentation of the buffer memory is a threat. It causes a gradual decrease in performance, which is critical in a long running process like the base station. The amount of fragmentation is different with different memory management methods. In this work the features and applicability of different memory management methods for signal processors used in the base stations of third generation cellular networks have been studied. Software based memory management includes a high amount of conditional branches. The signal processor, which is optimized for highly parallel sequential computing, executes conditional branches very badly when compared to microcontrollers and general-purpose processors. The memory management methods are first studied in theory and then experimentally. In the experiments two different memory management methods were analyzed. The memory managers were loaded with a synthetic workload program that simulates multi-user high bit-rate data transmissions in the base station. The performances of the memory managers were measured in terms of fragmentation, execution time and memory utilization. The experiments confirmed the information gained from the theoretical studies that different memory management methods are usually optimized for a certain feature. The experiments showed that a simple method is fast to execute and works well with small and intermediate loads. When the load is increased the performance decreases. The second, more complex, measured method was found to require more computing, but to be capable of using the memory space assigned to it more effectively.
EngD thesis: Reduced-Complexity Signal Detection in Digital Communications Receivers
The Author began this Engineering Doctorate (EngD) in Autumn 1999, whilst already in full-time employment as a DSP software engineer at Nortel Networks, Harlow. This EngD comprises a set of three projects. The first project was focused on the development of dual-tone multi-frequency (DTMF) signal detection software. DTMF signals are currently used for operating menu-driven services such as voice-mail, telephone banking and share-dealing. The need for detection software in a packet networking environment exists because such signals become degraded when they travel through speech compression circuits. In addition, if they appear as echoes on a telephone line, they can affect the operation of echo cancellation systems. In this thesis a number of DSP algorithms are discussed where fast detection and minimum complexity are key characteristics. A key contribution here was the development of a novel detection algorithm based on the extraction of parameters that model the DTMF signal. The thesis reports a method combining parameter extraction with the technique of maximum likelihood to perform DTMF detection, resulting in very short time-frames when compared to standard approaches. Reducing the complexity of detection techniques is also important in today’s communication systems. To this end a key contribution here was the development of the ‘split Goertzel algorithm’, which permitted an overlapping of analysis windows without the need for reprocessing input data. Besides being applied to voice-band signals, such as in the case of DTMF, the Author also had the opportunity during the EngD to apply the skills and knowledge acquired in signal processing to higher-rate data-streams. This involved work concerning the equalisation of channel distortion commonly found in wireless communication systems. This covers two projects, with the first being conducted at Verticalband Ltd. (now no longer operational) in the area of digital television receivers. In this part of the thesis a real-time DSP implementation is discussed for enhancing a simulation system developed for wireless channels. A number of channel equalisation approaches are studied. The work concludes that for high-rate signals, non-linear algorithms have the best error rate performance. On the basis of the studies carried out, the thesis considers development and implementation issues of designs based on the decision feedback equaliser. The thesis reports on a software design which applies the method of least squares to carry out filter coefficient adaptation. The Verticalband studies reported lead on to further research within the context of channel equalisation, in the context of the detection of data in multiple-input multiple-output (MIMO) wireless local area network (WLAN) systems. This work was undertaken at Philips Research in Eindhoven, The Netherlands. The thesis discusses implementation scenarios of multi-element antenna arrays that aim to provide bit-rates orders of magnitude higher than today’s WLAN offerings, as those required by emerging standards such as 802.11n. The complexity of optimal detection techniques, such as maximum likelihood, scales exponentially with the number of transmit antennas. This translates to high processing costs and power consumption, rendering such techniques unsuitable for use in battery-powered devices. The initial main contribution here was the analysis of the complexity of algorithms whose performance had already been tested, such as the non-linear maximum likelihood approach and also less complex methods utilising linear filtering. This resulted in the development of new formulae to predict processing costs of algorithms based on the number of transmit and receive antennas. Other key contributions were defining a method to reduce the complexity of matrix inversion when using the Moore-Penrose pseudo-inverse, and the application of matrix decomposition to obviate the need for costly matrix inversion at all. Some on-going research into sub-optimal detection is also discussed, which describes methods to reduce the search-space for the maximum likelihood algorithm.
A Subspace Based Approach to the Design, Implementation and Validation of Algorithms for Active Vibration Isolation Control
Vibration isolation endeavors to reduce the transmission of vibration energy from one structure (the source) to another (the receiver), to prevent undesirable phenomena such as sound radiation. A well-known method for achieving this is passive vibration isolation (PVI). In the case of PVI, mounts are used - consisting of springs and dampers - to connect the vibrating source to the receiver. The stiffness of the mount determines the fundamental resonance frequency of the mounted system and vibrations with a frequency higher than the fundamental resonance frequency are attenuated. Unfortunately, however, other design requirements (such as static stability) often impose a minimum allowable stiffness, thus limiting the achievable vibration isolation by passive means. A more promising method for vibration isolation is hybrid vibration isolation control. This entails that, in addition to PVI, an active vibration isolation control (AVIC) system is used with sensors, actuators and a control system that compensates for vibrations in the lower frequency range. Here, the use of a special form of AVIC using statically determinate stiff mounts is proposed. The mounts establish a statically determinate system of high stiffness connections in the actuated directions and of low stiffness connections in the unactuated directions. The latter ensures PVI in the unactuated directions. This approach is called statically determinate AVIC (SD-AVIC). The aim of the control system is to produce antidisturbance forces that counteract the disturbance forces stemming from the source. Using this approach, the vibration energy transfer from the source to the receiver is blocked in the mount due to the anti-forces. This thesis deals with the design of controllers generating the anti-forces by applying techniques that are commonly used in the field of signal processing. The control approaches - that are model-based - are both adaptive and fixed gain and feedforward and feedback oriented. The control approaches are validated using two experimental vibration isolation setups: a single reference single actuator single error sensor (SR-SISO) setup and a single reference input multiple actuator input multiple error sensor output (SR-MIMO) setup. Finding a plant model can be a problem. This is solved by using a black-box modelling strategy. The plants are identified using subspace model identification. It is shown that accurate linear models can be found in a straightforward manner by using small batches of recorded (sampled) time-domain data only. Based on the identified models, controllers are designed, implemented and validated. Due to resonance in mechanical structures, adaptive SD-AVIC systems are often hampered by slow convergence of the controller coefficients. In general, it is desirable that the SD-AVIC system yields fast optimum performance after it is switched on. To achieve this result and speed up the convergence of the adaptive controller coefficients, the so-called inverse outer factor model is included in the adaptive control scheme. The inner/outer factorization, that has to be performed to obtain the inverse outer factor model, is completely determined in state space to enable a numerically robust computation. The inverse outer factor model is also incorporated in the control scheme as a state space model. It is found that fast adaptation of the controller coefficients is possible. Controllers are designed, implemented and validated to suppress both narrowband and broadband disturbances. Scalar regularization is used to prevent actuator saturation and an unstable closed loop. In order to reduce the computational load of the controllers, several steps are taken including controller order reduction and implementation of lower order models. It is found that in all experiments the simulation and real-time results correspond closely for both the fixed gain and adaptive control situation. On the SR-SISO setup, reductions up to 5.0 dB are established in real-time for suppressing a broadband disturbance output (0-2 kHz) using feedback-control. On the SR-MIMO vibration isolation setup, using feedforward-control reductions of broadband disturbances (0-1 kHz) of 9.4 dB are established in real-time. Using feedback-control, reductions are established up to 3.5 dB in real-time (0-1 kHz). In case of the SR-MIMO setup, the values for the reduction are obtained by averaging the reductions obtained in all sensor outputs. The results pave the way for the next generation of algorithms for SD-AVIC.
Auditory System for a Mobile Robot
The auditory system of living creatures provides useful information about the world, such as the location and interpretation of sound sources. For humans, it means to be able to focus one's attention on events, such as a phone ringing, a vehicle honking, a person taking, etc. For those who do not suffer from hearing impairments, it is hard to imagine a day without being able to hear, especially in a very dynamic and unpredictable world. Mobile robots would also benefit greatly from having auditory capabilities. In this thesis, we propose an artificial auditory system that gives a robot the ability to locate and track sounds, as well as to separate simultaneous sound sources and recognising simultaneous speech. We demonstrate that it is possible to implement these capabilities using an array of microphones, without trying to imitate the human auditory system. The sound source localisation and tracking algorithm uses a steered beamformer to locate sources, which are then tracked using a multi-source particle filter. Separation of simultaneous sound sources is achieved using a variant of the Geometric Source Separation (GSS) algorithm, combined with a multisource post-filter that further reduces noise, interference and reverberation. Speech recognition is performed on separated sources, either directly or by using Missing Feature Theory (MFT) to estimate the reliability of the speech features. The results obtained show that it is possible to track up to four simultaneous sound sources, even in noisy and reverberant environments. Real-time control of the robot following a sound source is also demonstrated. The sound source separation approach we propose is able to achieve a 13.7 dB improvement in signal-to-noise ratio compared to a single microphone when three speakers are present. In these conditions, the system demonstrates more than 80% accuracy on digit recognition, higher than most human listeners could obtain in our small case study when recognising only one of these sources. All these new capabilities will allow humans to interact more naturally with a mobile robot in real life settings.
Auditory Component Analysis Using Perceptual Pattern Recognition to Identify and Extract Independent Components From an Auditory Scene
The cocktail party effect, our ability to separate a sound source from a multitude of other sources, has been researched in detail over the past few decades, and many investigators have tried to model this on computers. Two of the major research areas currently being evaluated for the so-called sound source separation problem are Auditory Scene Analysis (Bregman 1990) and a class of statistical analysis techniques known as Independent Component Analysis (Hyvärinen 2001). This paper presents a methodology for combining these two techniques. It suggests a framework that first separates sounds by analyzing the incoming audio for patterns and synthesizing or filtering them accordingly, measures features of the resulting tracks, and finally separates sounds statistically by matching feature sets and making the output streams statistically independent. Artificial and acoustical mixes of sounds are used to evaluate the signal-to-noise ratio where the signal is the desired source and the noise is comprised of all other sources. The proposed system is found to successfully separate audio streams. The amount of separation is inversely proportional to the amount of reverberation present.
Restoration of Nonlinearly Distorted Optical Soundtracks Using Regularized Inverse Characteristics
This dissertation is concerned with the possibilities of restoration of degraded film-sound. The sound-quality of old films are often not acceptable, which means that the sound is so noisy and distorted that the listener have to take strong efforts to understand the conversations in the film. In this case the film cannot give artistic enjoyment to the listener. This is the reason that several old films cannot be presented in movies or television. The quality of these films can be improved by digital restoration techniques. Since we do not have access to the original signal, only the distorted one, therefore we cannot adjust recording parameters or recording techniques. The only possibility is to post-compensate the signal to produce a better estimate about the undistorted, noiseless signal. In this dissertation new methods are proposed for fast and efficient restoration of nonlinear distortions in the optically recorded film soundtracks. First the nonlinear models and nonlinear restoration techniques are surveyed and the ill-posedness of nonlinear post-compensation (the extreme sensitivity to noise) is explained. The effects and sources of linear and nonlinear distortions at optical soundtracks are also described. A new method is proposed to overcome the ill-posedness of the restoration problem and to get an optimal result. The effectiveness of the algorithm is proven by simulations and restoration of real film-sound signals.
Through-Wall Imaging with UWB Radar System
Motivation: A man was interested in knowing of unknown from the very beginning of the human history. Our human eyes help us to investigate our environment by reflection of light. However, wavelengths of visible light allows transparent view through only a very small kinds of materials. On the other hand, Ultra WideBand (UWB) electromagnetic waves with frequencies of few Gigahertz are able to penetrate through almost all types of materials around us. With some sophisticated methods and a piece of luck we are able to investigate what is behind opaque walls. Rescue and security of the people is one of the most promising fields for such applications. Rescue: Imagine how useful can be information about interior of the barricaded building with terrorists and hostages inside for a policemen. The tactics of police raid can be build up on realtime information about ground plan of the room and positions of big objects inside. How useful for the firemen can be information about current interior state of the room before they get inside? Such hazardous environment, full of smoke with zero visibility, is very dangerous and each additional information can make the difference between life and death. Security: Investigating objects through plastic, rubber, dress or other nonmetallic materials could be highly useful as an additional tool to the existing x-ray scanners. Especially it could be used for scanning baggage at the airport, truckloads on borders, dangerous boxes, etc.
Efficient arithmetic for high speed DSP implementation on FPGAs
The author was sponsored by EnTegra Ltd, a company who develop hardware and software products and services for the real time implementation of DSP and RF systems. The field programmable gate array (FPGA) is being used increasingly in the field of DSP. This is due to the fact that the parallel computing power of such devices is ideal for today’s truly demanding DSP algorithms. Algorithms such as the QR-RLS update are computationally intensive and must be carried out at extremely high speeds (MHz). This means that the DSP processor is simply not an option. ASICs can be used but the expense of developing custom logic is prohibitive. The increased use of the FPGA in DSP means that there is a significant requirement for efficient arithmetic cores that utilises the resources on such devices. This thesis presents the research and development effort that was carried out to produce fixed point division and square root cores for use in a new Electronic Design Automation (EDA) tool for EnTegra, which is targeted at FPGA implementation of DSP systems. Further to this, a new technique for predicting the accuracy of CORDIC systems computing vector magnitudes and cosines/sines is presented. This work allows the most efficient CORDIC design for a specified level of accuracy to be found quickly and easily without the need to run lengthy simulations, as was the case before. The CORDIC algorithm is a technique using mainly shifts and additions to compute many arithmetic functions and is thus ideal for FPGA implementation.
A Prototype Laboratory Environment for Digital Signal Processing Using Simulink and a Texas Instrument DSP Device
Normally, when a model is designed from building blocks in Simulink, the simulation is performed within the Simulink environment. A test of the design in a real-time environment requires that source code is generated, compiled and downloaded to the target hardware. As a first attempt to bridge this software gap, this thesis describes and evaluates a prototype laboratory environment, which directly links Simulink to a Texas Instrument DSP device. The prototype system converts graphical models and makes available various real-time signal processing algorithms, such as adders, delays, FFTs, IIR filters and multipliers. Future work is to consider modification of the prototype to allow for feedback in the graphical models and to find an efficient way of handling signal processing algorithms where variable buffer lengths are required.
IMPLEMENTATION OF PERIODOGRAM SMOOTHING OF NOISYIMPLEMENTATION OF PERIODOGRAM SMOOTHING OF NOISY SIGNALS USING TMS320C6713 DSK
Periodogram Smoothing is a technique of power spectrum estimation. The discrete Fourier transform of a digital signal simply resolves the frequency components. The algorithm is implemented on Texas Instruments’ TMS320C6713 DSP Starter Kit (DSK). This is a 32-bit floating-point digital signal processor running at 225 MHz. The programs are basically written in the C programming language. However, those sections of code which are time-critical and memory-critical are written in assembly language of C6713. A MATLAB™ graphical user interface is also provided. The MATLAB™ program calls C programs loaded in Code Composer Studio (CCS). The C programs in turn call the assembly programs when required.
Noise covariance properties in Dual-Tree Wavelet Decompositions
Dual-tree wavelet decompositions have recently gained much popularity, mainly due to their ability to provide an accurate directional analysis of images combined with a reduced redundancy. When the decomposition of a random process is performed – which occurs in particular when an additive noise is corrupting the signal to be analyzed – it is useful to characterize the statistical properties of the dual-tree wavelet coefficients of this process. As dual-tree decompositions constitute overcomplete frame expansions, correlation structures are introduced among the coefficients, even when a white noise is analyzed. In this paper, we show that it is possible to provide an accurate description of the covariance properties of the dual-tree coefficients of a wide-sense stationary process. The expressions of the (cross-) covariance sequences of the coefficients are derived in the one and two-dimensional cases. Asymptotic results are also provided, allowing to predict the behaviour of the second-order moments for large lag values or at coarse resolution. In addition, the crosscorrelations between the primal and dual wavelets, which play a primary role in our theoretical analysis, are calculated for a number of classical wavelet families. Simulation results are finally provided to validate these results.
Wavelet Filter Banks in Perceptual Audio Coding
This thesis studies the application of the wavelet filter bank (WFB) in perceptual audio coding by providing brief overviews of perceptual coding, psychoacoustics, wavelet theory, and existing wavelet coding algorithms. Furthermore, it describes the poor frequency localization property of the WFB and explores one filter design method, in particular, for improving channel separation between the wavelet bands. A wavelet audio coder has also been developed by the author to test the new filters. Preliminary tests indicate that the new filters provide some improvement over other wavelet filters when coding audio signals that are stationary-like and contain only a few harmonic components, and similar results for other types of audio signals that contain many spectral and temporal components. It has been found that the WFB provides a flexible decomposition scheme through the choice of the tree structure and basis filter, but at the cost of poor localization properties. This flexibility can be a benefit in the context of audio coding but the poor localization properties represent a drawback. Determining ways to fully utilize this flexibility, while minimizing the effects of poor time-frequency localization, is an area that is still very much open for research.
Model Signal Impairments at Complex Baseband
In this article, we develop complex-baseband models for several signal impairments: interfering carrier, multipath, phase noise, and Gaussian noise. To provide concrete examples, we'll apply the impairments to a QAM system. The impairment models are Matlab functions that each use at most seven lines of code. Although our example system is QAM, the models can be used for any complex-baseband signal.
Design of a Scalable Polyphony-MIDI Synthesizer for a Low Cost DSP
In this thesis, the design of a music synthesizer implementing the Scalable Polyphony-MIDI soundset on a low cost DSP system is presented. First, the SP-MIDI standard and the target DSP platform are presented followed by review of commonly used synthesis techniques and their applicability to systems with limited computational and memory resources. Next, various oscillator and filter algorithms used in digital subtractive synthesis are reviewed in detail. Special attention is given to the aliasing problem caused by discontinuities in classical waveforms, such as sawtooth and pulse waves and existing methods for bandlimited waveform synthesis are presented. This is followed by review of established structures for computationally efficient time-varying filters. A novel digital structure is presented that decouples the cutoff and resonance controls. The new structure is based on the analog Korg MS-20 lowpass filter and is computationally very efficient and well suited for implementation on low bitdepth architectures. Finally, implementation issues are discussed with emphasis on the Differentiated Parabole Wave oscillator and MS-20 filter structures and the effects of limited computational capability and low bitdepth. This is followed by designs for several example instruments.
Signal Processing Requirements for WiMAX (802.16e) Base Station
802.16e provides specifications for non line of sight, mobile wireless communications in the frequency range of 2-6 GHz. It is well implemented by using OFDMA as its physical layer scheme. The OFDM symbol time (sT) is to be selected depending on the channel conditions, available bandwidth and, simulations provide a means of selecting right values of sTin different channel conditions. Additionally it has been shown that certain values of sT outperform others in all conditions, thus invalidating their use. Moreover, a solution proposed by INTEL is also analyzed. One of the major requirements of OFDM is high synchronization. Detecting the timing offset of a new mobile user, entering the network, which is not time aligned using cross-correlation and ‘auto-correlation’ in time domain and cross-correlation in frequency domain at the base station has been simulated. Results point that the processing load can be significantly reduced by using frequency domain correlation of the received data or by using ‘auto-correlation’ followed by cross-correlation on localized data. The use of adaptive antenna system in 802.16e improves the system performance, where beamforming is implemented in the direction of desired user. Capon’s method and MUSIC method have been simulated to compute the direction of arrival for OFDMA uplink. A new user, while in the ranging process, transmits data with unknown time offset and unknown direction. The thesis describes the procedure to find the two unknown one after another.
Implementing IS-95, the CDMA Standard, on TMS320C6201 DSP
IS-95 is the present U.S. 2nd generation CDMA standard. Currently, the 2nd generation CDMA phones are produced by Qualcomm. Texas Instruments (TI) has ASIC design for Viterbi Decoder on C54x. Several of the components in the forward link process are also implemented in hardware. However, having to design a specific hardware for a particular application is expensive and time consuming. Thus, the possibility of the alternative implementations is of great interest to both customers and TI itself. This research has achieved in successful implementation of IS-95 entirely in software on TI fixed-point DSP TMS320C6201, and met the real time constraint. IS-95 system, the industrial standard for CDMA, is a very complicated system and extremely computationally demanding. The transmission rate for an IS-95 system is 1.2288 Mcps. This research project includes all the major components of the demodulation process for the forward link system: PN Descrambling, Walsh Despreading, Phase Correction & Maximal Ratio Combining, Deinterleaver, Digital Automatic Gain Control, and Viterbi Deccc:r. The entire demodulation process is done completely in C. That makes it a very attractive alternative implementation in the future applications. It is well known that ASIC design is not only expensive and but also time consuming, programming in assembly is easier and cheaper, but programming in C is a much easier and efficient way out, in particular, for general computer engineers. During the whole process, efforts have been devoted on developing various specific techniques to optimize the design for all the components involved. These developments are successfully achieved by making the best use of the following techniques: to simplify the algorithms first before programming, to look for regularity in the problem, to work toward the Compiler's full efficiency, and to use C intrinsics whenever possible. All these attributes together make the implementation scheme great for DSP applications. The benchmark results compare very well to the TI-internal hand scheduled assembly performance of the same type of decoders. The estimated percentage usage of all the components (excluding PN) is only 21.18% of the total CPU cycles available (4,000 K), which is very efficient and impressive.
Efficient Signal Processing Techniques for Future Wireless Communications Systems
Wireless communications systems are evolving to be more diverse in use and more ubiquitous in nature. It is of fundamental importance that we consume the resources available in such systems, i.e., bandwidth and energy, to preserve room for more users and to preserve longevity. Signal processing can greatly help us achieve this. In this thesis we consider improving the utility of resources available in wireless communications systems. The basic obstacle for most wireless communications systems is the multipath channel that causes intersymbol interference. Channel estimation is a crucial step for recovering the transmitted symbols. Moreover, as more devices are equipped with wireless capabilities, the bandwidth becomes scarce and it is important to allow more than one device or more than one user to use the same frequency range or the same channel. However, this introduces multiuser interference, which is again eliminated only if the channel is known. Furthermore, most wireless systems are battery powered, at least at the transmitter end. Hence it is crucial that energy consumption is minimized to preserve the longevity of the system. The contribution of this thesis is three fold: (i) We propose novel bandwidth efficient blind channel estimation algorithms for single input multiple output systems, and for multiuser OFDM systems. The former exploits cyclostationarity inherent in communications signals. The latter exploits the structure introduced to the transmitted signal via precoding. We consider design of such precoders by optimizing performance metrics such as the bit error rate and signal to interference plus noise ratio. (ii) In the multiuser systems case, we propose a novel cooperative OFDM system and show that, when users face significantly different channel conditions, cooperation can improve the performance of all the cooperating users. (iii) We consider energy efficient training based system estimation in large MIMO systems. The goal there is to minimize energy consumption both in transmission of training symbols and in performing computations. We show that by using a divide and conquer strategy in selecting the active set of transmitters and receivers, it is possible to minimize energy consumption without degrading the accuracy of the channel estimate.
