Signal detection in communication systems under uncertainty environment

Abstract

Signal detection models in communication applications are mostly developed based on hypothesis test using a statistical parametric model. The hypothesis test, such as Neyman-Pearson test and likelihood ratio test, models the observation space by using statistical distribution, which is only optimal when the system modeling including both transmission and modulation is represented accurately, and all values of the parameters used in the models are known precisely. However, due to the inherent uncertainties in both the system model and the system parameters, the performance of the detection systems in practice is usually well below the expectation. Fuzzy logic, which coordinates imprecise information by fuzzy set theory, is a simple but effective approach to model uncertainties in signal detection. In this thesis, a fuzzy approach in signal detection for handling the uncertainties is discussed, and is demonstrated in pulse detection, Phase Shift Keying (PSK) demodulation, chaos-based communication system, and Ultra-Wide Band (UWB) communication detection. Pulse detection often examines the magnitude of the signal and makes a decision on the existence of that pulse by using hypothesis test, such as Neyman-Pearson test. Binary Integrator (BI) is a common and yet fundamental method for enhancing the performance of detection by integrating a series of pulses for the decision when there are more than one pulse. In Chapter 2, a Fuzzy Integration (FI) detection scheme, based on the binary integrator is reviewed. The Fuzzy Integration detection scheme is discussed and presented, and the performance of the FI detection and the BI are compared. The inherent robustness characteristic of the FI detection scheme is also demonstrated by comparing it with that of a conventional Neyman-Pearson detector. The performance of the PSK detector, using parametric model, may also be degraded by the imprecision of the system modeling. Chapter 3 presents a fuzzy hypothesis test catering for the imprecise parameters as fuzzy numbers, and shows how this can be applied to the PSK detector. The performance of the PSK detector due to imprecision is also analyzed. Results illustrate to what extent the performance would vary due to the degree of parameter imprecision. A PSK detector using fuzzy clustering, aiming at resolving uncertainty in the phase noise problem and the I/Q impairments of the PSK modulator, is presented in Chapter 4. The fuzzy clustering scheme is developed by considering the Euclidean distance between the centroid of a cluster and the received symbol in the constellation diagram graphically. Analysis results show that the performance of the proposed detector approaches that of the classical optimal detector where the latter does not consider any phase noise or I/Q impairment, and outperforms the classical detector in the case of high signal-to-noise ratios with phase noise and I/Q impairment of the modulator. In Chapter 5, the concept of fuzzy integration as discussed in Chapter 2 is further applied to chaos-based digital communication systems for detection performance improvement in the presence of impulse noise during the transmission. Fuzzy integration in chaos-based digital communication systems is discussed and its performance is evaluated for Chaos-Shift-Keying (CSK) and Differential Chaos-Shift-Keying (DCSK) system under both single-user and multiple-user environments. The analysis in this chapter illustrates that the fuzzy integration detection method in both CSK and DCSK performs better than the conventional detection method in situations with impulse noises. Ultra-Wide Band (UWB) Impulse Radio (IR) with spread-spectrum technique is one of the most recently developing technologies in digital communication systems. In a multi-users environment, performance of UWB system can be adversely affected by Multi-Access Interference (MAI), where MAI can also be treated as a kind of imprecision of the noise model. In Chapter 6, a fuzzy detector for Time-Hopping Spread-Spectrum (TH-SS) Pulse-Position Modulation (PPM) in UWB system is discussed and presented. Analysis result demonstrates that the FI detector can significantly improve the BER performance under multi-access scenario. In the last chapter, a general discussion is presented concluding the use of fuzzy logic in four different areas in signal detection applications as discussed in Chapters 2 to 6. By performing Monte Carlo simulations of the fuzzy approach in signal detection, the result shows that the fuzzy approach could outperform the classical detector under uncertainty scenario, and has a robust characteristic.

Date of Award	15 Jul 2005
Original language	English
Awarding Institution	City University of Hong Kong
Supervisor	Sai Wing Peter LEUNG (Supervisor)