| dc.description.abstract | Green communication has received significant attention and discussions due to its potential
telecom business, recent technology advances, and environmental protection. Saving
energy and harvesting energy are two main perspectives to improve the energy consumption of
wireless communication networks. In this dissertation, we focus on the green designs for two
kinds of wireless networks, namely, heterogeneous networks (HetNets) and wireless-powered
communication networks (WPCNs) from these two perspectives through resource management
and beamforming techniques. For the green HetNets, we investigate a macrocell-assisted small
cell network that allows for saving energy consumption by dynamically switching off the deployed
small cells and offloading the data traffic to the macrocell base station. The power-saving
strategy of the macrocell-assisted small cell networks depends on several network parameters
like power consumption of base stations, available bandwidth, user load in the cells, cell size,
user rate requirement, rate outage probability, and noise power density. Besides, it also affects
the user dropping probability of the small cells. For the WPCNs, we investigate a wireless
network that can utilize energy harvesting technology to capture wireless energy and convert
it into electrical energy that can be used immediately or later. Specifically, we consider that
wireless-powered devices can harvest energy from radio-frequency signals by the base station
in the downlink and then utilize the harvested energy for transmitting data in the uplink. The
base station can concurrently serve multiple users with downlink harvested energy and uplink
data reception by utilizing beamforming techniques. The designed WPCN, however, suffers
from several critical issues such as power control, uplink multiuser interference, power transfer
efficiency, and base station energy consumption.
For the macrocell-assisted small cell networks, the design problem is formulated as a constrained
Markov decision process and solved via linear programming. A randomized strategy is proposed to accomplish the optimal sleep/wake-up policy for small cells. For the WPCNs, the
downlink/uplink beamforming, downlink/uplink time allocation, and uplink multiuser power
control are jointly designed. The non-convex problem is first solved with fixed time allocation
and uplink receive beamforming via a semi-definite relaxation (SDR) approach, based on
which an iterative algorithm is proposed for updating the optimal time allocation and the receive
beamforming. The proposed design methodologies are validated via extensive computer simulations.
The simulation results confirm that the proposed Markov decision process approach can
achieve efficient energy utilization by switching on/off small cells while ensuring the average
user dropping probability. Also, the simulation results confirm that the proposed joint resource
management and beamforming scheme can effectively reduce the charging energy consumption
of the base station. | en_US |