4,332 research outputs found
A Max-Min Task Offloading Algorithm for Mobile Edge Computing Using Non-Orthogonal Multiple Access
To mitigate computational power gap between the network core and edges,
mobile edge computing (MEC) is poised to play a fundamental role in future
generations of wireless networks. In this letter, we consider a non-orthogonal
multiple access (NOMA) transmission model to maximize the worst task to be
offloaded among all users to the network edge server. A provably convergent and
efficient algorithm is developed to solve the considered non-convex
optimization problem for maximizing the minimum number of offloaded bits in a
multi-user NOMAMEC system. Compared to the approach of optimized orthogonal
multiple access (OMA), for given MEC delay, power and energy limits, the
NOMA-based system considerably outperforms its OMA-based counterpart in MEC
settings. Numerical results demonstrate that the proposed algorithm for
NOMA-based MEC is particularly useful for delay sensitive applications.Comment: 5 pages, 5 figure
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
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