论文标题
在反向散射辅助无线驱动的MEC网络中，计算位最大化
Computation Bits Maximization in a Backscatter Assisted Wirelessly Powered MEC Network
论文作者
论文摘要
在本文中，我们引入了一个反向散射辅助的无线移动边缘计算（MEC）网络，每个边缘用户（EU）可以通过混合收获-then-transmit（HTT）和反向分散通信将任务位卸载到MEC服务器。特别是，考虑到每个欧盟的实用非线性能量收集（EH）模型和部分卸载方案，我们提出了一个方案，通过共同优化后镜反射系数和时间，主动传输功率和时间，本地计算频率和每个EU的执行时间，以最大化所有EU的加权总和计算位。通过引入一系列辅助变量并使用非线性EH模型的属性，我们将原始的非凸问题转换为凸一个问题，并为最佳解决方案的一部分提供了封闭形式表达式。仿真结果证明了所提出的方案在加权总和计算位方面的优势而不是基准方案。
In this paper, we introduce a backscatter assisted wirelessly powered mobile edge computing (MEC) network, where each edge user (EU) can offload task bits to the MEC server via hybrid harvest-then-transmit (HTT) and backscatter communications. In particular, considering a practical non-linear energy harvesting (EH) model and a partial offloading scheme at each EU, we propose a scheme to maximize the weighted sum computation bits of all the EUs by jointly optimizing the backscatter reflection coefficient and time, active transmission power and time, local computing frequency and execution time of each EU. By introducing a series of auxiliary variables and using the properties of the non-linear EH model, we transform the original non-convex problem into a convex one and derive closedform expressions for parts of the optimal solutions. Simulation results demonstrate the advantage of the proposed scheme over benchmark schemes in terms of weighted sum computation bits.
