面向UAV辅助MEC场景的NOMA解码方法研究

Research on NOMA decoding methods for UAV-assisted MEC scenarios

  • 摘要: 针对无人机辅助移动边缘计算应急通信场景,因非正交多址(non-orthogonal multiple access,NOMA)的连续干扰消除(serial interference cancellation, SIC)解码排序会影响用户的任务完成时间和限制上行任务卸载链路传输性能而造成系统能耗高的问题,提出一种基于用户优先级的NOMA无人机辅助移动边缘计算算法. 首先,建立一种基于用户优先级的SIC解码排序算法;然后,在此基础上联合计算资源分配、发射功率建立一个最小化系统加权总能耗问题;最后,由于该优化问题的非凸性,采用连续凸近似方法和二次逼近将目标函数转化为凸优化问题. 仿真实验结果表明,相较信道增益解码排序方式, 基于用户优先级的连续干扰消除解码排序接入方式能更有效降低系统能耗,降低的能耗约为3.38%.

     

    Abstract: In the context of unmanned aerial vehicles-assisted mobile edge computing for emergency communication scenarios, the issue of high system energy consumption arises due to the impact of serial interference cancellation decoding order in non-orthogonal multiple access on users' task completion time and the limitation of uplink task offloading link transmission performance. To address this, a non-orthogonal multiple access UAV-assisted mobile edge computing algorithm based on user priority is proposed. Firstly, a Serial Interference Cancellation decoding order algorithm based on user priority is established. Secondly, by jointly considering computational resource allocation and transmission power, a problem aimed at minimizing the system's weighted total energy consumption is formulated. Finally, due to the non-convex nature of this optimization problem, the successive convex approximation method and quadratic transformation are employed to convert the objective function into a convex optimization problem. Simulation results demonstrate that, compared to the channel gain-based decoding order approach, the user priority-based SIC decoding order access method can more effectively reduce system energy consumption, achieving a reduction of approximately 3.38%.

     

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