The data traffic in cellular networks has had and will experience a rapid exponential
rise. Therefore, it is essential to innovate a new cellular architecture with
advanced wireless technologies that can offer more capacity and enhanced spectral
efficiency to manage the exponential data traffic growth. Managing such mass
data traffic, however, brings up another challenge of increasing energy consumption.
This is because it contributes into a growing fraction of the carbon dioxide
(CO2) emission which is a global concern today due to its negative impact on
the environment. This has resulted in creating a new paradigm shift towards both
spectral and energy efficient orientated design for the next-generation wireless access
networks. Acquiring both improved energy efficiency and spectral efficiency
has, nonetheless, shown to be a difficult goal to achieve as it seems improving one
is at the detriment to the other. Therefore, the trade-off between the spectral and
energy efficiency is of paramount importance to assess the energy consumption in
a wireless communication system required to attain a specific spectral efficiency.
This thesis looks into this problem. It studies the spectral-energy efficiency tradeoff
for some of the emerging wireless communication technologies which are seen
as potential candidates for the fifth generation (5G) mobile cellular system. The
focus is on the orthogonal frequency division multiple access (OFDMA), mobile
femtocell (MFemtocell), cognitive radio (CR), and the spatial modulation (SM).
Firstly, the energy-efficient resource allocation scheme for multi-user OFDMA
(MU-OFDMA) system is studied. The spectral-energy efficiency trade-off is
analysed under the constraint of maintaining the fairness among users. The
energy-efficient optimisation problem has been formulated as integer fractional
programming. We then apply an iterative method to simplify the problem to an
integer linear programming (ILP) problem.
Secondly, the spectral and energy efficiency for a cellular system with MFemtocell
deployment is investigated using different resource partitioning schemes.
Femtocells are low range, low power base stations (BSs) that improve the coverage
inside a home or office building. MFemtocell adopts the femtocell solution to be deployed in public transport and emergency vehicles. Closed-form expressions
for the relationships between the spectral and energy efficiency are derived for
a single-user (SU) MFemtocell network. We also study the spectral efficiency
for MU-MFemtocells with two opportunistic scheduling schemes.
Thirdly, the spectral-energy efficiency trade-off for CR networks is analysed at
both SU and MU CR systems against varying signal-to-noise ratio (SNR) values.
CR is an innovative radio device that aims to utilise the spectrum more efficiently
by opportunistically exploiting underutilised licensed spectrum. For the SU system,
we study the required energy to achieve a specific spectral efficiency for a
CR channel under two different types of power constraints in different fading environments.
In this scenario, interference constraint at the primary receiver (PR)
is also considered to protect the PR from harmful interference. At the system
level, we study the spectral and energy efficiency for a CR network that shares
the spectrum with an indoor network. Adopting the extreme-value theory, we
are able to derive the average spectral efficiency of the CR network.
Finally, we propose two innovative schemes to enhance the capability of (SM). SM
is a recently developed technique that is employed for a low complexity multipleinput
multiple-output (MIMO) transmission. The first scheme can be applied for
SU MIMO (SU-MIMO) to offer more degrees of freedom than SM. Whereas the
second scheme introduces a transmission structure by which the SM is adopted
into a downlink MU-MIMO system. Unlike SM, both proposed schemes do not
involve any restriction into the number of transmit antennas when transmitting
signals. The spectral-energy efficiency trade-off for the MU-SM in the massive
MIMO system is studied. In this context, we develop an iterative energy-efficient
water-filling algorithm to optimises the transmit power and achieve the maximum
energy efficiency for a given spectral efficiency.
In summary, the research presented in this thesis reveals mathematical tools to
analysis the spectral and energy efficiency for wireless communications technologies.
It also offers insight to solve optimisation problems that belong to a class
of problems with objectives of enhancing the energy efficiency
