Exploitation of signal information for mobile speed estimation and anomaly detection
Afgani, Mostafa Z.
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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.