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
