Mukasa, Constantine

Relationships
Member of: Graduate College
Person Preferred Name
Mukasa, Constantine
Model
Digital Document
Publisher
Florida Atlantic University
Description
In wireless communications systems, it is well known that the instantaneous
received signal is a random variable that follows a given distribution. The randomness
mainly stems from e ects such as multipath fading, shadowing, and interference.
The received signal is a relevant metric, such that several distributions have been
used in the literature to characterize it. However, as new radio technologies emerge,
the known distributions are deemed insu cient to t simulated and measure data.
Subsequently, as the wireless industry moves onto the fth generation (5G), newer
distributions are proposed to well represent the received signal for new wireless technologies,
including those operating in the millimeter-wave (mmWave) band. These
are mainly application speci c and may not be adequate to model complex 5G devices
performance. Therefore, there is a need to unify and generalize the received signal
distributions used for performance analysis of wireless systems.
Secondly, an explosion of new radio technologies and devices operating in the
same limited radio spectrum to collect and share data at alarming rates is expected.
Such an explosion coupled with the 5G promise of ubiquitous connectivity and network
densi cation, will thrust interference modeling in dense networks to the fore-front. Thus, interference characterization is essential when analyzing such wireless
networks.
Thirdly, the classical distributions used to model the received signal do not
account for the inherent mobility feature for emerging radio technologies, such as
avionics systems (e.g. drones), which may make the distributions inadequate as mobility
e ects can no longer be ignored.
Consequently, in this dissertation, we propose the use of a unifying distribution,
the Fox's H-function distribution, with subsume ability to represent several
traditional and future distributions, as a statistical tool to evaluate the performance
of wireless communications systems. Additionally, two interference models, one with
a xed number and the other with a random number of interferers, are considered to
derive interference statistics, and further utilize the results to analyze system performance
under the e ect of interference. Finally, we extend the classical distributions
to include the mobility regime for several wireless network topologies, and perform
network analysis. The analytical results are validated using computer Monte Carlo
simulations.
Model
Digital Document
Publisher
Florida Atlantic University
Description
In wireless systems such as cellular systems, frequency reuse is employed to extend the
coverage area but this process introduces undesirable co-channel interference. A tradeoff must be
made between increasing system capacity and transmission quality when planning, designing and
deploying such wireless systems. In order to meet the explosive demand for high data rate
wireless services for a growing population within a given geographical area, future wireless
cellular networks will adopt smaller cells, such as femtocells, that are serviced by low-power
base stations. As the deployment of femto-cellular base stations rapidly increases in the coming
years, interference coordination and management will be the primary challenge in such
heterogeneous networks. In this work, we derive a novel closed form expression for the
cumulative distribution function CDF and coverage probability for a small cell wireless network
operating in a Nakagami fading environment in the presence of Gaussian noise and impulsive
interference modeled as an alpha-stable process. With these results, we can determine the
probabilistic access thresholds that provide the best probable tradeoff between system capacity
and network quality.
Model
Digital Document
Publisher
Florida Atlantic University
Description
In recent years, a plethora of wireless applications such as Bluetooth and Ultra-wide band (UWB) radio have emerged. This drastic increase has overly congested the spectrum. So, new networks such as cognitive radios that can solve the spectrum congestion have emerged. But in such networks, interference is introduced at the physical layer. We study and develop an interference model capable of capturing the intrinsic characteristics of the coexistence of such wireless applications. We investigate the effect of interference using device isolation probability or outage probability in presence Rayleigh and Nakagami-m fading at the physical layer and the impact of lognormal shadowing. We assume that the devices are either deterministically placed or randomly distributed according to a Poisson point process. We derive explicit expressions for the isolation probability and outage probability that give insight into how these channel impairments affect communication in these applications. We use computer simulations to validate our analytical results.