In this dissertation, power allocation approaches considering path loss, shadowing,
and Rayleigh and Nakagami-m fading are proposed. The goal is to improve power
consumption, and energy and throughput efficiency based on user target signal to interference plus noise ratio (SINR) requirements and an outage probability threshold.
First, using the moment generating function (MGF), the exact outage probability
over Rayleigh and Nakagami-m fading channels is derived. Then upper and lower
bounds on the outage probability are derived using the Weierstrass, Bernoulli and
exponential inequalities. Second, the problem of minimizing the user power subject
to outage probability and user target SINR constraints is considered. The corresponding power allocation problems are solved using Perron-Frobenius theory and
geometric programming (GP). A GP problem can be transformed into a nonlinear
convex optimization problem using variable substitution and then solved globally and
efficiently by interior point methods. Then, power allocation problems for throughput
maximization and energy efficiency are proposed. As these problems are in a convex
fractional programming form, parametric transformation is used to convert the original problems into subtractive optimization problems which can be solved iteratively.
Simulation results are presented which show that the proposed approaches are better
than existing schemes in terms of power consumption, throughput, energy efficiency
and outage probability.
Prioritized cell association and power allocation (CAPA) to solve the load balancing issue in heterogeneous networks (HetNets) is also considered in this dissertation.
A Hetnet is a group of macrocell base stations (MBSs) underlaid by a diverse set
of small cell base stations (SBSs) such as microcells, picocells and femtocells. These
networks are considered to be a good solution to enhance network capacity, improve
network coverage, and reduce power consumption. However, HetNets are limited
by the disparity of power levels in the different tiers. Conventional cell association
approaches cause MBS overloading, SBS underutilization, excessive user interference
and wasted resources. Satisfying priority user (PU) requirements while maximizing
the number of normal users (NUs) has not been considered in existing power allocation algorithms. Two stage CAPA optimization is proposed to address the prioritized
cell association and power allocation problem. The first stage is employed by PUs
and NUs and the second stage is employed by BSs. First, the product of the channel
access likelihood (CAL) and channel gain to interference plus noise ratio (GINR) is considered for PU cell association while network utility is considered for NU cell association. Here, CAL is defined as the reciprocal of the BS load. In CAL and GINR
cell association, PUs are associated with the BSs that provide the maximum product
of CAL and GINR. This implies that PUs connect to BSs with a low number of users
and good channel conditions. NUs are connected to BSs so that the network utility
is maximized, and this is achieved using an iterative algorithm. Second, prioritized
power allocation is used to reduce power consumption and satisfy as many NUs with
their target SINRs as possible while ensuring that PU requirements are satisfied.
Performance results are presented which show that the proposed schemes provide fair
and efficient solutions which reduce power consumption and have faster convergence
than conventional CAPA schemes. / Graduate
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/11065 |
| Date | 26 August 2019 |
| Creators | Ho, Danh Huu |
| Contributors | Gulliver, T. Aaron |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
| Rights | Available to the World Wide Web |
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