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Switched mode, Class-D power amplification allows for high efficiency power amplification of an audio signal. This thesis investigates its application to high power car audio systems where there is a demand for efficient high power amplification. Examination of the present car audio power amplifiers, which comprise a switched mode power supply combined with a linear output stage, has shown that there is significant scope for improvement in efficiency and power density. A novel power stage in which the attributes of a switched-mode power supply and full bridge output stage is presented. It is demonstrated that elimination of the intermedjate DC supply results in an amplifier which has a significantly lower part count, size and cost compared to conventional designs. Two different modulation schemes are explored (PWM and PDM) with a view to finding the most suitable for the new power stage. The theoretical performances of the modulators are verified by practical measurements. The design of high order DeltaSigma modulators is difficult as they show unstable behaviour and an alternative design methodology has been presented to ease this task. The mechanisms which introduce distortion in a practical amplifier are discussed, and for the case of a PWM driven output stage, a new model is presented to predict the effect of dead time on harmonic distortion. This form of distortion is shown to be the dominant cause of open loop non-linearity. The use of feedback is also investigated and yields a factor of 20 improvement in amplifier total harmonic distortion . The design throughout has been supported with practical results and these have illustrated the importance for careful circuit layout in high frequency switching systems.

Location estimation when deployed on wireless networks supports a range of services including user tracking and monitoring, health care support and push and pull marketing. The main subject of this thesis is improving indoor and outdoor location estimation accuracy using received signal strength (RSS) from neighbouring base stations (BSs) or access points (APs), without using the global positioning system (GPS) or triangulation methods. For the outdoor environment, state-of-the-art deterministic and probabilistic algorithms are adapted to exploit principal components (PCs) and clustering. The accuracy is compared with K-nearest neighbour (KNN) algorithms using different partitioning models. The proposed scheme clusters the RSS tuples based on deviations from an estimated RSS attenuation model and then transforms the raw RSS in each cluster into new uncorrelated dimensions, using PCs. As well as simple global dimensionality reduction using PCs, the data reduction and rotation within each cluster improves estimation accuracy because a) each cluster can model the different local RSS distributions and b) it efficiently preserves the RSS correlations that are observed (some of which are substantial) in local regions and which independence approximations ignore. Different simulated and real environments are used for the comparisons. Experimental results show that positioning accuracy is significantly improved and fewer training samples are needed compared with traditional methods. Furthermore, a technique to adjust RSS data so that radio maps collected in different environmental conditions can be used together to enhance accuracy is also demonstrated. Additionally, in the radio coverage domain, a non-parametric probability approach is used for the radio reliability estimation and a semi-supervised learning model is proposed for the monitoring model training and evolution according to real-time mobile users’ RSS feedback. For the indoor environment, an approach for a large multi-story indoor location estimaiii tion using clustering and rank order matching is described. The accuracies using WiFi RSS alone, cellular GSM RSS alone and integrated WiFi and GSM RSS are presented. The methods were tested on real indoor environments. A hierarchical clustering method is used to partition the RSS space, where a cluster is defined as a set of mobile users who share exactly the same strongest RSS ranking set of transmitters. The experimental results show that while integrating of WiFi RSS with GSM RSS creates a marginal improvement, the GSM data can be used to ameliorate the loss of accuracy when APs fail.