354 research outputs found
Positioning of multiple unmanned aerial vehicle base stations in future wireless network
Abstract. Unmanned aerial vehicle (UAV) base stations (BSs) can be a reliable and efficient alternative to full fill the coverage and capacity requirements when the backbone network fails to provide the requirements during temporary events and after disasters. In this thesis, we consider three-dimensional deployment of multiple UAV-BSs in a millimeter-Wave network. Initially, we defined a set of locations for a UAV-BS to be deployed inside a cell, then possible combinations of predefined locations for multiple UAV-BSs are determined and assumed that users have fixed locations. We developed a novel algorithm to find the feasible positions from the predefined locations of multiple UAVs subject to a signal-to-interference-plus-noise ratio (SINR) constraint of every associated user to guarantees the quality-of-service (QoS), UAV-BS’s limited hovering altitude constraint and restricted operating zone because of regulation policies. Further, we take into consideration the millimeter-wave transmission and multi-antenna techniques to generate directional beams to serve the users in a cell.
We cast the positioning problem as an ℓ₀ minimization problem. This is a combinatorial, NP-hard, and finding the optimum solution is not tractable by exhaustive search. Therefore, we focused on the sub-optimal algorithm to find a feasible solution. We approximate the ℓ₀ minimization problem as non-combinatorial ℓ₁-norm problem. The simulation results reveal that, with millimeter-wave transmission the positioning of the UAV-BS while satisfying the constrains is feasible. Further, the analysis shows that the proposed algorithm achieves a near-optimal location to deploy multiple UVABS simultaneously
Energy sustainable paradigms and methods for future mobile networks: A survey
In this survey, we discuss the role of energy in the design of future mobile
networks and, in particular, we advocate and elaborate on the use of energy
harvesting (EH) hardware as a means to decrease the environmental footprint of
5G technology. To take full advantage of the harvested (renewable) energy,
while still meeting the quality of service required by dense 5G deployments,
suitable management techniques are here reviewed, highlighting the open issues
that are still to be solved to provide eco-friendly and cost-effective mobile
architectures. Several solutions have recently been proposed to tackle
capacity, coverage and efficiency problems, including: C-RAN, Software Defined
Networking (SDN) and fog computing, among others. However, these are not
explicitly tailored to increase the energy efficiency of networks featuring
renewable energy sources, and have the following limitations: (i) their energy
savings are in many cases still insufficient and (ii) they do not consider
network elements possessing energy harvesting capabilities. In this paper, we
systematically review existing energy sustainable paradigms and methods to
address points (i) and (ii), discussing how these can be exploited to obtain
highly efficient, energy self-sufficient and high capacity networks. Several
open issues have emerged from our review, ranging from the need for accurate
energy, transmission and consumption models, to the lack of accurate data
traffic profiles, to the use of power transfer, energy cooperation and energy
trading techniques. These challenges are here discussed along with some
research directions to follow for achieving sustainable 5G systems.Comment: Accepted by Elsevier Computer Communications, 21 pages, 9 figure
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