Abstract:
Wireless spectrum has become a scarce resource due to the exponential growth of
the number and type of devices that utilize the electromagnetic spectrum. The cost of
long term leasing of spectrum has proven to be a major road block in efficient use of
frequency spectrum. Moreover, spectrum measurement studies have shown that
substantial portions of the allocated wireless spectrum are highly underutilized. Thus,
Dynamic Spectrum Access (DSA) devices have been proposed to be allowed to share the
spectrum dynamically between users. The idea is that the DSA devices will continuously
scan the spectrum and start to transmit in a channel when a licensed user’s operation is
not detected in that channel. Detailed path loss models are needed to calculate the
propagation loss between a DSA device transmitter and a licensed user receiver in order
for the DSA device to avoid causing interference to the receiver by using overly high
transmit power levels.
This thesis proposes a novel propagation loss model called Location Based
Propagation Modeling (LPM) based on the existing TIREM path loss model. The TIREM
model gives the median value of the path loss for a given transmitter and receiver pair
and the user needs to know the precise locations of the transmitter and receiver to
calculate the path loss with the TIREM model. However, for DSA applications, we
usually do not know the precise locations of the licensed user receivers. Furthermore,
TIREM model requires detailed terrain information stored in the memory to calculate
path loss, but DSA devices have limited memory. As a result, we need a compact
representation of the TIREM model which gives the path loss without the need to store
terrain information in the memory. These were the motivations to develop the LPM.
DSA devices require accurate spectral estimation methods to determine whether a
channel is occupied in a specific time and location. Two spectral estimation methods:
multitaper spectral estimation method and conventional FFT-based spectral estimation
method are compared in this thesis using real signal measurements. Our numerical results
show that the multitaper approach yields a significant increase in the number of harvested
channels, while maintaining a smaller probability of false alarm.
