1,909 research outputs found
On the Performance and Optimization for MEC Networks Using Uplink NOMA
In this paper, we investigate a non-orthogonal multiple access (NOMA) based
mobile edge computing (MEC) network, in which two users may partially offload
their respective tasks to a single MEC server through uplink NOMA. We propose a
new offloading scheme that can operate in three different modes, namely the
partial computation offloading, the complete local computation, and the
complete offloading. We further derive a closed-form expression of the
successful computation probability for the proposed scheme. As part of the
proposed offloading scheme, we formulate a problem to maximize the successful
computation probability by jointly optimizing the time for offloading, the
power allocation of the two users and the offloading ratios which decide how
many tasks should be offloaded to the MEC server. We obtain the optimal
solutions in the closed forms. Simulation results show that our proposed scheme
can achieve the highest successful computation probability than the existing
schemes.Comment: This paper has been accepted by IEEE ICC Workshop 201
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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