9 research outputs found
User Association in 5G Networks: A Survey and an Outlook
26 pages; accepted to appear in IEEE Communications Surveys and Tutorial
Integrated Data and Energy Communication Network: A Comprehensive Survey
OAPA In order to satisfy the power thirsty of communication devices in the imminent 5G era, wireless charging techniques have attracted much attention both from the academic and industrial communities. Although the inductive coupling and magnetic resonance based charging techniques are indeed capable of supplying energy in a wireless manner, they tend to restrict the freedom of movement. By contrast, RF signals are capable of supplying energy over distances, which are gradually inclining closer to our ultimate goal – charging anytime and anywhere. Furthermore, transmitters capable of emitting RF signals have been widely deployed, such as TV towers, cellular base stations and Wi-Fi access points. This communication infrastructure may indeed be employed also for wireless energy transfer (WET). Therefore, no extra investment in dedicated WET infrastructure is required. However, allowing RF signal based WET may impair the wireless information transfer (WIT) operating in the same spectrum. Hence, it is crucial to coordinate and balance WET and WIT for simultaneous wireless information and power transfer (SWIPT), which evolves to Integrated Data and Energy communication Networks (IDENs). To this end, a ubiquitous IDEN architecture is introduced by summarising its natural heterogeneity and by synthesising a diverse range of integrated WET and WIT scenarios. Then the inherent relationship between WET and WIT is revealed from an information theoretical perspective, which is followed by the critical appraisal of the hardware enabling techniques extracting energy from RF signals. Furthermore, the transceiver design, resource allocation and user scheduling as well as networking aspects are elaborated on. In a nutshell, this treatise can be used as a handbook for researchers and engineers, who are interested in enriching their knowledge base of IDENs and in putting this vision into practice
Energy efficiency optimization in millimeter wave backhaul heterogeneous networks
Within the last few years, there has been a massive growth in the number of wireless
devices and internet connections. This is expected to continue during the next
few years. To satisfy the resulting high data traffic demands, dramatic expansion of
network infrastructures as well as fast escalation of energy demands are expected.
Meanwhile, there has been a growing concern about the energy consumption of wireless
communication systems and their global carbon footprint. To that end, future
wireless systems must satisfy three main requirements. Firstly, they must provide
users with very high throughput. Secondly, they must be able to provide seamless
connectivity as well as ubiquitous access to the expected enormous number of users.
Finally, they must achieve the first two points with less energy consumption. The requirements
can be summarized into the joint optimization of energy efficiency (EE),
user association and backhaul (BH) flow assignment, which remains a fundamental
objective in the design of next generation networks.
This thesis consists of two studies on EE maximization in heterogeneous networks
(HetNets). In the first study, it is assumed that each user has already been associated
to a single base station (BS). Under this setting, We consider enforcing a strict
throughput demand on all user equipment (UEs), called joint EE, power, and flow
control (JEEPF), versus allowing an acceptable range of demands for each, called joint
EE, power, flow control, and throughput (JEEPFT). This minor change causes a drastic difference in the formulation of both problems. JEEPF is convex while JEEPFT is
quasiconvex, for which we propose a bisection method-based approach. In the second
study, the problem of user association is added to the joint optimization of EE, power
and BH flow control, and an energy efficient user association, power and flow control
(EEUAPF) algorithm is proposed. The original EEUAPF optimization problem is a
non-convex mixed integer programming problem, and therefore NP-hard. We show
how this non-convex problem can be tailored into a form that can be approached
using a classical mathematical programming technique called column generation and
convex programming to derive the optimal solution with a low complexity.
Simulation results are used to demonstrate the EE gains of the proposed approaches
in both studies