Signal processing--Digital techniques

We developed a cross layer design which combines retransmission diversity and
multi-user diversity for wireless communication. To this end, a joint design of
adaptive modulation and coding with retransmission-based automatic repeat request
protocol is outlined. This design is applied to devise multi-user scheduling schemes,
which can optimally capture the available multi-user and retransmission diversities. In
addition, the proposed on-line scheduling algorithms can operate even when the
underl ying fading channel distribution is unknown, while asymptotically converging
to the offline benchmark with guarantees on prescribed fairness and rate requirements.
Numerical results are provided to verify the merits of our novel schemes for
multi-user transmissions over Nakagami block fading channels.

A daily study spanning a month of the shallow water acoustic channel was conducted to
estimate the environmental influence on performance of an underwater acoustic communications
system. An automated acoustic modem transmitted phase-coherent modulated sequences of
identical data with 186 dB re IpPa source level, at coded rates from 4000 to 16000 bits/s with
4 or 8 kHz symbol bandwidth, three times daily for a month. A 64 channel Mills-Cross receiver
array was used with horizontal and vertical beams each containing 32 and 33 elements
respectively, spaced 0.03 meters apart, with a sampling frequency of 72 kHz. Source and
receiver were deployed at depths of 20 meters respectively, with a 720 meter separation range.
Environmental measurements of wind velocity and direction, surface wave activity, current and
sound velocity profiles, and tidal measurements were performed. Results demonstrate reliable
achievement of high data-rate shallow water acoustic communications using phase-coherent
modulation techniques.

Society's increased demand for communications requires searching for techniques that preserve bandwidth. It has been observed that much of the time spent during telephone communications is actually idle time with no voice activity present. Detecting these idle periods and preventing transmission during these idle periods can aid in reducing bandwidth requirements during high traffic periods. While techniques exist to perform this detection, certain types of noise can prove difficult at best for signal detection. The use of wavelets with multi-resolution subspaces can aid detection by providing noise whitening and signal matching. This thesis explores its use and proposes a technique for detection.

The design of any communication receiver needs to addresses the issues of operating under the lowest possible signal-to-noise ratio. Among various algorithms that facilitate this objective are those used for iterative decoding of two-dimensional systematic convolutional codes in applications such as spread spectrum communications and Code Division Multiple Access (CDMA) detection. A main theme of any decoding schemes is to approach the Shannon limit in signal-to-noise ratio. All these decoding algorithms have various complexity levels and processing delay issues. Hence, the optimality depends on how they are used in the system. The technique used in various decoding algorithms is termed as iterative decoding. Iterative decoding was first developed as a practical means for decoding turbo codes. With the Log-Likelihood algebra, it is shown that a decoder can be developed that accepts soft inputs as a priori information and delivers soft outputs consisting of channel information, a posteriori information and extrinsic information to subsequent stages of iteration. Different algorithms such as Soft Output Viterbi Algorithm (SOVA), Maximum A Posteriori (MAP), and Log-MAP are compared and their complexities are analyzed in this thesis. A turbo decoder is implemented on the Digital Signal Processing (DSP) chip, TMS320C30 by Texas Instruments using a Modified-Log-MAP algorithm. For the Modified-Log-MAP-Algorithm, the optimal choice of the lookup table (LUT) is analyzed by experimenting with different LUT approximations. A low complexity decoder is proposed for a (7,5) code and implemented in the DSP chip. Performance of the decoder is verified under the Additive Wide Gaussian Noise (AWGN) environment. Hardware issues such as memory requirements and processing time are addressed for the chosen decoding scheme. Test results of the bit error rate (BER) performance are presented for a fixed number of frames and iterations.

This study deals with applying the wavelet transform to mainly two different areas of signal processing: adaptive signal processing, and signal detection. It starts with background information on the theory of wavelets with an emphasis on the multiresolution representation of signals by the wavelet transform in Chapter 1. Chapter 2 begins with an overview of adaptive filtering in general and extends it to transform domain adaptive filtering. Later in the chapter, a novel adaptive filtering architecture using the wavelet transform is introduced. The performance of this new structure is evaluated by using the LMS algorithm with variations in step size. As a result of this study, the wavelet transform based adaptive filter is shown to reduce the eigenvalue ratio, or condition number, of the input signal. As a result, the new structure is shown to have faster convergence, implying an improvement in the ability to track rapidly changing signals. Chapter 3 deals with signal detection with the help of the wavelet transform. One scheme studies signal detection by projecting the input signal onto different scales. The relationship between this approach and that of matched filtering is established. Then the effect of different factors on signal detection with the wavelet transform is examined. It is found that the method is robust in the presence of white noise. Also, the wavelets are analyzed as eigenfunctions of a certain random process, and how this gives way to optimal receiver design is shown. It is further demonstrated that the design of an optimum receiver leads to the wavelet transform based adaptive filter structure described in Chapter 2.

Currently, our acoustic modems are used to communicate underwater to Autonomous Underwater Vehicles AUVs. These modems have only one sensor and can transmit at low data rates (from 200 to 1200 bits per second) using Frequency Shift Keying (FSK) modulation. A two-dimensional array receiver (MillsCross) has been developed to receive underwater signals with more reliability, at a higher data rate (about 30,000 bits per second). This array has been designed to operate with Phase Shift Keying modulated signals. The purpose of this thesis is to design and implement a signal processing software to demodulate and decode FSK signals acquired by the MillsCross. By taking advantage of the spatial gain of the MillsCross receiver array, higher reliability and longer ranges are expected using FSK, in addition to achieving compatibility between the two systems. This software includes a robust synchronization scheme, a spatial and an equalizing filter, a time-window self-adjusting process and the error control decoding.

Based on the theoretical method developed by Clark and Greenstein for frequency-selective Rayleigh fading channel, we develop a general model for frequency-selective Nakagami fading channel. We derive analytical expressions of the average bit-error-rate in an ideal space diversity mobile radio receiver using the matched filter bound. Our simulation results show that the influences of the diversity order, the shape of the multipath delay profile, and delay spread of the multipath delay profile. Five shapes are considered in our simulation. Our simulation results highlight the importance of the ratio the normalized delay spread d. The results show that the delay profile is of no importance for $d<0.3,$ but can have a profound influence for $d\geq0.3.$

This thesis presents a comprehensive analysis of a relatively new transform for discrete time signals, called the Discrete Wavelet Transform (DWT). We find how this transform is connected with the already existing theory of perfect reconstruction filter banks and the recently introduced theory of multiresolution analysis. We use the conditions obtained from these two theories in order to understand the construction of wavelet filters, which also generate continuous functions that prove to constitute an orthonormal basis for the L$\sp2$ space. We also investigate the connection of this transform to the sampled wavelet series of nonorthogonal functions with good time-frequency localization properties. Finally, we see the way that the DWT maps a discrete signal in the phase plane and the applications that such representations incorporate.

This thesis describes a software model of a Linear Predictive Coding (L.P.C.) that is written in the Ada language. The novel feature of this program is that it attempts to execute the maximum possible number of concurrent arithmetic operations in the L.P.C. algorithm. Each arithmetic operation is implemented by an active process which is the "task" construct in the Ada language. The computational part of the algorithm is implemented as a wavefront array of computing tasks. These computational arrays are driven by a driver task which coordinates the flow of data into and out of the computing surfaces. If the inter process communications time between tasks is small, then this model shows a potential for speed-up. If this be the case, one may conclude that this model is an appropriate implementation for a linear predictive coding.

The purpose of this thesis is to show the use of digital techniques for Electronic Countermeasures (ECM) signal processing. The main objective is the use of only digital circuitry for the processing of the ECM signals. A recent design of an ECM controller called the Oscillator Waveform Controller (OWC) follows this philosophy. The OWC digitally controls the generation of its nine jamming modes plus the modes generated by the other ECM modules within the ECM system. The use of advance microcircuitry technology allows the OWC the capability of controlling all the parameters within an ECM system. The most desirable feature of the OWC is the use of high level communications for programming ECM mode parameters from an external computer or terminal and digitally storing this parameters upon removal of power.