3,221 research outputs found
Joint optimization of transmission and propulsion in aerial communication networks
Communication energy in a wireless network of mobile autonomous agents should be considered as the sum of transmission energy and propulsion energy used to facilitate the transfer of information. Accordingly, communication-theoretic and Newtonian dynamic models are developed to model the communication and locomotion expenditures of each node. These are subsequently used to formulate a novel nonlinear optimal control problem (OCP) over a network of autonomous nodes. It is then shown that, under certain conditions, the OCP can be transformed into an equivalent convex form. Numerical results for a single link between a node and access point allow for comparison with known solutions before the framework is applied to a multiple-node UAV network, for which previous results are not readily extended. Simulations show that transmission energy can be of the same order of magnitude as propulsion energy allowing for possible savings, whilst also exemplifying how speed adaptations together with power control may increase the network throughput
Mobile Edge Computing via a UAV-Mounted Cloudlet: Optimization of Bit Allocation and Path Planning
Unmanned Aerial Vehicles (UAVs) have been recently considered as means to
provide enhanced coverage or relaying services to mobile users (MUs) in
wireless systems with limited or no infrastructure. In this paper, a UAV-based
mobile cloud computing system is studied in which a moving UAV is endowed with
computing capabilities to offer computation offloading opportunities to MUs
with limited local processing capabilities. The system aims at minimizing the
total mobile energy consumption while satisfying quality of service
requirements of the offloaded mobile application. Offloading is enabled by
uplink and downlink communications between the mobile devices and the UAV that
take place by means of frequency division duplex (FDD) via orthogonal or
non-orthogonal multiple access (NOMA) schemes. The problem of jointly
optimizing the bit allocation for uplink and downlink communication as well as
for computing at the UAV, along with the cloudlet's trajectory under latency
and UAV's energy budget constraints is formulated and addressed by leveraging
successive convex approximation (SCA) strategies. Numerical results demonstrate
the significant energy savings that can be accrued by means of the proposed
joint optimization of bit allocation and cloudlet's trajectory as compared to
local mobile execution as well as to partial optimization approaches that
design only the bit allocation or the cloudlet's trajectory.Comment: 14 pages, 5 figures, 2 tables, IEEE Transactions on Vehicular
Technolog
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