In this paper, we investigate the resource allocation of mobile edge computing (MEC) in cognitive capacity harvesting networks (CCHNs) when non-orthogonal multiple-access (NOMA) technique is adopted. Different from traditional studies for NOMA-MEC networks, we aim at minimizing the total cost of CCHN while satisfying the quality-of-service (QoS) of secondary users (SUs). We adopt the mechanism of time division multiple access (TDMA) when several NOMA groups use the same spectrum, and consider both the waiting delay and transmission delay during data offloading with the optimization of transmission order of NOMA groups. We formulate the considered problem as a mixed integer non-linear programming (MINLP). We show that the transmit power and the allocated computing resource for each SU can be derived when the transmission time and transmission order of the NOMA groups are given. Based on this, the considered problem can be decomposed into a transmission time and order optimization subproblem, a cellular resource block (CRB) selection subproblem and a cognitive radio (CR) router selection subproblem. To solve the transmission time and order optimization subproblem, we first simplify the delay constraint via theoretic analysis, and then propose a binary segmentation (B-Seg) algorithm and a transmission order adjustment (TOA) algorithm to find the optimal transmission time and transmission order of NOMA groups, respectively. To solve the CRB selection subproblem and the CR router selection subproblem, a bigger requirement first (BRF) algorithm and a game-based iteration (GBI) algorithm are respectively proposed. Simulation results show that the proposed algorithms can significantly improve the system performance.

中文翻译：

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基于 TDMA-NOMA 的基于传输顺序优化的认知容量收集网络的计算卸载

在本文中，我们研究了采用非正交多址 (NOMA) 技术时认知容量收集网络 (CCHN) 中移动边缘计算 (MEC) 的资源分配。与对 NOMA-MEC 网络的传统研究不同，我们旨在最小化 CCHN 的总成本，同时满足二级用户 (SU) 的服务质量 (QoS)。当多个NOMA组使用相同的频谱时，我们采用时分多址（TDMA）机制，并考虑数据卸载过程中的等待延迟和传输延迟，优化NOMA组的传输顺序。我们将所考虑的问题表述为混合整数非线性规划（MINLP）。我们表明，当给定 NOMA 组的传输时间和传输顺序时，可以推导出每个 SU 的传输功率和分配的计算资源。基于此，所考虑的问题可以分解为传输时间和顺序优化子问题、蜂窝资源块（CRB）选择子问题和认知无线电（CR）路由器选择子问题。为了解决传输时间和顺序优化子问题，我们首先通过理论分析简化延迟约束，然后提出二进制分段（B-Seg）算法和传输顺序调整（TOA）算法来寻找最优传输时间和传输顺序NOMA 组，分别。为了解决 CRB 选择子问题和 CR 路由器选择子问题，分别提出了更大的需求优先（BRF）算法和基于博弈的迭代（GBI）算法。仿真结果表明，所提出的算法可以显着提高系统性能。