ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada / Shaped Offset Quadrature Shift Keying (SOQPSK) is a spectrally efficient modulation that has been promoted in the airborne telemetry community as a more spectrally efficient alternative for legacy PCM/FM. First generation demodulators for SOQPSK use coherent detectors which achieve good bit error rates at the expense of long synchronization times. This paper examines the performance of a noncoherent SOQPSK detector which significantly improves the signal acquisition times without impacting BER performance in the AWGN environment. The two detection methods are also compared in their ability to combat other channel impairments, such as adjacent and on-channel interference.

International Telemetering Conference Proceedings / October 23-26, 2000 / Town & Country Hotel and Conference Center, San Diego, California / Binary PCM/FM has been widely adopted as a standard by the telemetry community. It offers a reasonable balance between detection efficiency and spectral efficiency, with very simple implementation in both the transmitter and receiver. Current technology, however, allows practical implementations of more sophisticated demodulators, which can substantially improve the detection efficiency of the waveform, with no changes to the modulator. This is accomplished by exploiting the memory inherent in the phase continuity of the waveform. This paper describes the implementation and performance of a noncoherent multi-symbol demodulator for PCM/FM. Sensitivity to offsets in carrier frequency, timing, and modulation index is also examined. Simulation results are presented which demonstrate improvements in detection efficiency of approximately 2.5 dB over traditional noncoherent single symbol detectors.

International Telemetering Conference Proceedings / October 22-25, 2001 / Riviera Hotel and Convention Center, Las Vegas, Nevada / It has been previously shown, through computer simulations, that a multiple symbol detector can provide substantial gains in detection efficiency (nearly 3 dB) over traditional PCM/FM detectors. This is accomplished by performing correlations over multiple symbol intervals to take advantage of the memory inherent in the continuous phase PCM/FM signal. This paper presents measured hardware results, from a prototype developed for the Advanced Range Telemetry (ARTM) Project, that substantiate the previously published performance and sensitivity predictions. Furthermore, this work confirms the feasibility of applying this technology to high-speed commercial and military telemetry applications.

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International Telemetering Conference Proceedings / October 21, 2002 / Town & Country Hotel and Conference Center, San Diego, California / This paper presents noncoherent limiter-discriminator detection and differential detection of FQPSK (Feher quadrature phase-shift-keying) with maximum-likelihood sequence estimation (MLSE) techniques. Noncoherent FQPSK systems are suitable for fast fading and cochannel interference channels and channels with strong phase noise, and they can offer faster synchronization and reduce outage events compared with conventional coherent systems. In this paper, both differential detection and limiter-discriminator detection of FQPSK are discussed. We use MLSE with lookup tables to exploit the memory in noncoherently detected FQPSK signals and thus significantly improve the bit error rate (BER) performance in an additive white Gaussian noise (AWGN) channel.

UWB communication is an attractive technology that has the potential to provide low-power, low-complexity, and high-speed communications in short range links. One of the main challenges of the UWB communications is the highly frequency-selective channel, which induces hundreds of overlapped copies of the transmitted pulse with different delays and amplitudes. To collect the energy of these multipath components, coherent Rake receivers are proposed, but suffer from high implementation and computational costs on channel estimation. To avoid the stringent channel estimation, several noncoherent receivers, including energy detector (ED) and transmitted reference (TR), are proposed at the cost of degraded performance. In addition, when taking into account practical issues of UWB communications, e.g., non-Gaussian impulsive noise, non-ideal antennas, and limited, significant performance degradation may be introduced by noncoherent receivers. In this dissertation, we will present low-complexity, high-performance, noncoherent receiver designs for UWB communications that i) avoid the stringent channel estimation; ii) lower the computational complexity of the existing receivers with the aid of advanced digital signal processing techniques; and iii) improve the error performance of the noncoherent receivers by accommodating practical imperfections. First, we propose three multi-symbol detectors (MSDs) for multi-symbol different detection (MSDD), which has recently caught attention in UWB communications because of its high performance without requiring explicit channel estimation. To alleviate the non-deterministic polynomial hardness (NP-hard) of MSDD, we analyze the statistical model of MSDD and propose an iterative MSD and two MSDs based on relaxation technique with near-optimal performance and low complexity. Moreover, the error performance of MSDs is further enhanced by exploiting joint soft-input soft-output MSDD and forward error correction codes. Next, we consider the non-Gaussian noise in the presence of multi-access interference, which is impulsive when the number of active users is small. To mitigate the impulsive noise effect, in this dissertation, we propose new differential UWB receivers based on the generalized Gaussian distribution and Laplace distribution and achieve better error performance. Another main issue of UWB communications is the limited radio coverage. To extend the coverage and improve the performance of UWB systems, we focus on a novel differentially encoded decode-and-forward (DF) non-cooperative relaying scheme. Putting emphasis on the general case of multi-hop relaying, we illustrate a novel algorithm for the joint power allocation and path selection (JPAPS), minimizing an approximate of the overall bit error rate (BER). A simplified scheme is also presented, which reduces the complexity to O(N²) and achieves a negligible performance loss. Finally, we concentrate on code-multiplexing (CM) systems, which have recently drawn attention mainly because they enable noncoherent detection without requiring either a delay component, as in TR, or an analog carrier, as in frequency-shifted reference. In this dissertation, we propose a generalized code-multiplexing (GCM) system based on the formulation of a constrained mixed-integer optimization problem. The GCM extends the concept of existing CM while retaining their simple receiver structure, even offering better BER performance and a higher data rate in the sense that more data symbols can be embedded in each transmitted block. Moreover, the impacts of non-ideal antennas on the GCM systems are investigated given some practical antenna measurement data and IEEE 802.15.4a channel environments.

<p>This thesis is concerned with detection of transient signal families and detectors in nonlinear static sensor systems. The detection problems are treated within the framework of likelihood ratio based binary hypothesis testing.</p><p>An analytical solution to the noncoherent detection problem is derived, which in contrast to the classical noncoherent detector, is optimal for wideband signals. An optimal detector for multiple transient signals with unknown arrival times is also derived and shown to yield higher detection performance compared to the classical approach based on the generalized likelihood ratio test.</p><p>An application that is treated in some detail is that of ultrasonic nondestructive testing, particularly pulse-echo detection of defects in elastic solids. The defect detection problem is cast as a composite hypothesis test and a methodology, based on physical models, for designing statistically optimal detectors for cracks in elastic solids is presented. Detectors for defects with low computational complexity are also formulated based on a simple phenomenological model of the defect echoes. The performance of these detectors are compared with the physical model-based optimal detector and is shown to yield moderate performance degradation.</p><p>Various aspects of optimal detection in static nonlinear sensor systems are also treated, in particular the stochastic resonance (SR) phenomenon which, in this context, implies noise enhanced detectability. Traditionally, SR has been quantified by means of the signal-to-noise ratio (SNR) and interpreted as an increase of a system's information processing capability. Instead of the SNR, rigorous information theoretic distance measures, which truly can support the claim of noise enhanced information processing capability, are proposed as quantifiers for SR. Optimal detectors are formulated for two static nonlinear sensor systems and shown to exhibit noise enhanced detectability.</p>

This thesis is concerned with detection of transient signal families and detectors in nonlinear static sensor systems. The detection problems are treated within the framework of likelihood ratio based binary hypothesis testing. An analytical solution to the noncoherent detection problem is derived, which in contrast to the classical noncoherent detector, is optimal for wideband signals. An optimal detector for multiple transient signals with unknown arrival times is also derived and shown to yield higher detection performance compared to the classical approach based on the generalized likelihood ratio test. An application that is treated in some detail is that of ultrasonic nondestructive testing, particularly pulse-echo detection of defects in elastic solids. The defect detection problem is cast as a composite hypothesis test and a methodology, based on physical models, for designing statistically optimal detectors for cracks in elastic solids is presented. Detectors for defects with low computational complexity are also formulated based on a simple phenomenological model of the defect echoes. The performance of these detectors are compared with the physical model-based optimal detector and is shown to yield moderate performance degradation. Various aspects of optimal detection in static nonlinear sensor systems are also treated, in particular the stochastic resonance (SR) phenomenon which, in this context, implies noise enhanced detectability. Traditionally, SR has been quantified by means of the signal-to-noise ratio (SNR) and interpreted as an increase of a system's information processing capability. Instead of the SNR, rigorous information theoretic distance measures, which truly can support the claim of noise enhanced information processing capability, are proposed as quantifiers for SR. Optimal detectors are formulated for two static nonlinear sensor systems and shown to exhibit noise enhanced detectability.

The objective of this research work is to develop reliable and power-efficient synchronization algorithms for continuous phase modulation (CPM). CPM is a bandwidth and power efficient signaling scheme suitable for wireless and mobile communications. Binary CPM schemes have been widely used in many commercial and military systems. CPM with multilevel symbol inputs, i.e., M-ary CPM, can achieve a higher data rate than binary CPM. However, the use of M-ary CPM has been limited due to receiver complexity and synchronization problems. In the last decade, serially concatenated CPM (SCCPM) has drawn more attention since this turbo-like coded scheme can achieve near Shannon-limit performance by performing iterative demodulation/decoding. Note that SCCPM typically operates at a low signal-to-noise ratio, which makes reliable and power-efficient synchronization more challenging. In this thesis, we propose a novel timing and phase recovery technique for CPM. Compared to existing maximum-likelihood estimators, the proposed data-aided synchronizer can achieve a better acquisition performance when a preamble is short or channel model errors are present. We also propose a novel adaptive soft-input soft-output (A-SISO) module for iterative detection with parameter uncertainty. In contrast to the existing A-SISO algorithms using linear prediction, the parameter estimation in the proposed structure is performed in a more general least-squares sense. Based on this scheme, a family of fixed-interval A-SISO algorithms are utilized to implement blind iterative phase synchronization for SCCPM. Moreover, the convergence characteristics of iterative phase synchronization and detection are analyzed by means of density evolution. Particularly, an oscillatory convergence behavior is observed when cycle slips occur during phase tracking. In order to reduce performance degradation due to this convergence fluctuation, design issues, including delay depth of the proposed algorithms, iteration-stopping criteria and interleaver size, are also discussed. Finally, for completeness of the study on phase synchronization, we investigate the error probability performance of noncoherently detected full-response CPM, which does not require channel (or phase) estimation.