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Resource Allocation for Low-Latency Mobile Edge Computation Offloading in NOMA Networks

机译:NOMA网络中用于低延迟移动边缘计算卸载的资源分配

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In this paper, we investigate the resource allocation for mobile edge computation offloading in non-orthogonal multiple access (NOMA) cellular networks. Leveraging NOMA, the massive connectivity can be supported to enable multiple cellular users to simultaneously upload their computation-intensive tasks on the same orthogonal resources, which improves spectral efficiency and reduces transmission delay. However, the co-channel interference in non- orthogonal spectrum sharing may potentially degrade the achievable rate of offloading computation tasks. Moreover, the overall delay of all cellular users in finishing computation offloading will increase if the computation resources at the edge server are not properly allocated. To minimize the maximum overall delay of all users, we formulate an optimization problem that jointly allocates communication resources and computation resources. Due to the non-convexity of the primal problem, we divide it into three subproblems. By exploiting their specific structures, an efficient algorithm is designed to obtain the suboptimal solution with low computational complexity. Simulation results are presented to demonstrate that our proposed algorithm can effectively reduce the overall delay of cellular users and fully exploit the benefit of NOMA on spectral efficiency, especially when the number of users is large.
机译:在本文中,我们研究了非正交多址(NOMA)蜂窝网络中用于移动边缘计算卸载的资源分配。利用NOMA,可以支持大规模连接,从而使多个蜂窝用户可以在相同的正交资源上同时上传其计算密集型任务,从而提高了频谱效率并减少了传输延迟。然而,非正交频谱共享中的同信道干扰可能潜在地降低卸载计算任务的可实现速率。而且,如果边缘服务器处的计算资源没有适当分配,则所有蜂窝用户在完成计算卸载方面的总延迟将增加。为了最小化所有用户的最大总延迟,我们制定了一个优化问题,该问题可以联合分配通信资源和计算资源。由于原始问题的非凸性,我们将其分为三个子问题。通过利用它们的特定结构,设计了一种有效的算法来以较低的计算复杂度获得次优解决方案。仿真结果表明,该算法可以有效减少蜂窝用户的总体时延,并充分利用NOMA在频谱效率方面的优势,特别是在用户数量较大的情况下。

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