在基于上行非正交多址接入(NOMA)的无人机(UAV)辅助移动边缘计算(MEC)系统中,NOMA的连续干扰消除(SIC)顺序已成为限制上行任务卸载链路传输性能的瓶颈,为降低系统能耗,对 SIC 顺序进行了讨论,提出了联合信道增益与任务时延约束的最优SIC顺序.在满足设备给定任务时延、设备最大发射功率约束以及UAV轨迹的约束下,基于最优SIC顺序提出了最小化系统能耗的问题.由于该问题是个复杂的非凸问题,采取交替优化的方法求解该优化问题,以实现功率分配和 UAV 轨迹的优化;利用匹配理论,提出了低复杂度算法来得到不同时隙的最优设备分组.仿真结果表明,与其他SIC顺序相比,最优SIC顺序能够在相同的任务时延约束下实现更小的系统能耗;所提的低复杂度设备分组算法能够得到最优设备分组.
Energy consumption optimization scheme in UAV-assisted MEC system based on optimal SIC order
In uplink non-orthogonal multiple access(NOMA)-based unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC)system,the successive interference cancellation(SIC)order of NOMA became a bottleneck lim-iting the transmission performance of task offload in uplink link.To reduce the energy consumption of the system,the SIC order was discussed and the optimal SIC order based on channel gain and task delay constraint was proposed.The optimization problem of minimizing the system energy consumption was proposed based on the optimal SIC order while satisfying the constraints of the given task delay of the device,the maximum transmit power constraint of the device,and the UAV trajectory.Since the problem was a complex non-convex problem,an alternating optimization method was adopted to solve the optimization problem to achieve power allocation and UAV trajectory optimization.A low-complexity algorithm based on matching theory was proposed to obtain the optimal device grouping in different time slots.Simulation results show that the optimal SIC order can realize smaller system energy consumption under the same task delay constraint compared with other SIC order,the proposed low-complexity device grouping algorithm can obtain the optimal device grouping.
万方数据
维普
