Exploitation of signal information for mobile speed estimation and anomaly detection

Although the primary purpose of the signal received by amobile handset or smartphone is to enable wireless communication, the information extracted can be reused to provide a number of additional services. Two such services discussed in this thesis are: mobile speed estimation and signal anomaly detection. The proposed algorithms exploit the propagation environment specific information that is already imprinted on the received signal and therefore do not incur any additional signalling overhead. Speed estimation is useful for providing navigation and location based services in areas where global navigation satellite systems (GNSS) based devices are unusable while the proposed anomaly detection algorithms can be used to locate signal faults and aid spectrum sensing in cognitive radio systems. The speed estimation algorithms described within this thesis require a receiver with at least two antenna elements and a wideband radio frequency (RF) signal source. The channel transfer function observed at the antenna elements are compared to yield an estimate of the device speed. The basic algorithm is a one-dimensional and unidirectional two-antenna solution. The speed of the mobile receiver is estimated from a knowledge of the fixed inter-antenna distance and the time it takes for the trailing antenna to sense similar channel conditions previously observed at the leading antenna. A by-product of the algorithm is an environment specific spatial correlation function which may be combined with theoretical models of spatial correlation to extend and improve the accuracy of the algorithm. Results obtained via computer simulations are provided. The anomaly detection algorithms proposed in this thesis highlight unusual signal features while ignoring events that are nominal. When the test signal possesses a periodic frame structure, Kullback-Leibler divergence (KLD) analysis is employed to statistically compare successive signal frames. A method of automatically extracting the required frame period information from the signal is also provided. When the signal under test lacks a periodic frame structure, information content analysis of signal events can be used instead. Clean training data is required by this algorithm to initialise the reference event probabilities. In addition to the results obtained from extensive computer simulations, an architecture for field-programmable gate array (FPGA) based hardware implementations of the KLD based algorithm is provided. Results showing the performance of the algorithms against real test signals captured over the air are also presented. Both sets of algorithms are simple, effective and have low computational complexity – implying that real-time implementations on platforms with limited processing power and energy are feasible. This is an important quality since location based services are expected to be an integral part of next generation cognitive radio handsets

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Quality-Oriented Mobility Management for Multimedia Content Delivery to Mobile Users

The heterogeneous wireless networking environment determined by the latest developments in wireless access technologies promises a high level of communication resources for mobile computational devices. Although the communication resources provided, especially referring to bandwidth, enable multimedia streaming to mobile users, maintaining a high user perceived quality is still a challenging task. The main factors which affect quality in multimedia streaming over wireless networks are mainly the error-prone nature of the wireless channels and the user mobility. These factors determine a high level of dynamics of wireless communication resources, namely variations in throughput and packet loss as well as network availability and delays in delivering the data packets. Under these conditions maintaining a high level of quality, as perceived by the user, requires a quality oriented mobility management scheme. Consequently we propose the Smooth Adaptive Soft-Handover Algorithm, a novel quality oriented handover management scheme which unlike other similar solutions, smoothly transfer the data traffic from one network to another using multiple simultaneous connections. To estimate the capacity of each connection the novel Quality of Multimedia Streaming (QMS) metric is proposed. The QMS metric aims at offering maximum flexibility and efficiency allowing the applications to fine tune the behavior of the handover algorithm. The current simulation-based performance evaluation clearly shows the better performance of the proposed Smooth Adaptive Soft-Handover Algorithm as compared with other handover solutions. The evaluation was performed in various scenarios including multiple mobile hosts performing handover simultaneously, wireless networks with variable overlapping areas, and various network congestion levels