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Distributed Resource Allocation and Computation Offloading Scheme for Cognitive Mobile Edge Computing Networks with NOMA

机译:具有NOMA的认知移动边缘计算网络的分布式资源分配与计算卸载方案

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Mobile edge computing (MEC) has become a key component of 5G, via bringing computation services to the edge of the mobile network to enhance the computational capacity of users. To improve spectrum efficiency, we adopt cognitive radio (CR) technology in the MEC system, which makes the resource allocation and computation offloading problem more complex. In this paper, we consider a multi-MEC and multi-user system combined with CR, where each user has a computation task to complete. To further improve the system efficiency, non-orthogonal multiple access (NOMA) is adopted by users. We formulate the resource allocation and computation offloading problem in our scenario as an optimization problem with multiple constraints which aims to maximize the system utility. Alternating direction method of multipliers (ADMM) is adopted to solve this problem in a distributed and efficient way. Simulation results show that our algorithm could achieve great performance comparing to state-of-art distributed and centralized approaches.
机译:移动边缘计算(MEC)已成为5G的关键组件,通过将计算服务带到移动网络的边缘,以增强用户的计算能力。为了提高频谱效率,我们在MEC系统中采用认知无线电(CR)技术,这使得资源分配和计算卸载问题更复杂。在本文中,我们考虑一个多MEC和多用户系统与CR组合,其中每个用户都有一个计算任务完成。为了进一步提高系统效率,用户采用了非正交多次访问(NOMA)。我们在我们的场景中制定资源分配和计算卸载问题作为具有多个约束的优化问题,该系统旨在最大化系统实用程序。采用乘体(ADMM)的交替方向方法以分布式和有效的方式解决此问题。仿真结果表明,我们的算法可以实现与最先进的分布式和集中方法相比的良好性能。

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