This article studies the strategic interactions between an IoT service provider (IoTSP) which consists of heterogeneous IoT devices and its energy service provider (ESP). To that end, we propose an economic framework using the Stackelberg game to maximize the network throughput and energy efficiency of both the IoTSP and ESP. To obtain the Stackelberg equilibrium (SE), we apply a backward induction technique which first derives a closed-form solution for the ESP (follower). Then, to tackle the non-convex optimization problem for the IoTSP (leader), we leverage the block coordinate descent and convex-concave procedure techniques to design two partitioning schemes (i.e., partial adjustment (PA) and joint adjustment (JA)) to find the optimal energy price and service time that constitute local SEs. Numerical results reveal that by jointly optimizing the energy trading and time allocation for IoT devices, one can achieve significant improvements in terms of the IoTSP’s profit compared with those of conventional transmission methods (up to 38.7 folds). Different tradeoffs between the ESP’s and IoTSP’s profits and complexities of the PA/JA schemes can also be numerically tuned. Simulations also show that the obtained local SEs approach the optimal social welfare when the benefit per transmitted bit exceeds a given threshold.

中文翻译：

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异构无线供电和基于反向散射的物联网网络的时间调度和能源交易


本文研究由异构物联网设备组成的物联网服务提供商（IoTSP）与其能源服务提供商（ESP）之间的战略交互。为此，我们提出了一个使用 Stackelberg 博弈的经济框架，以最大限度地提高 IoTSP 和 ESP 的网络吞吐量和能源效率。为了获得 Stackelberg 平衡 (SE)，我们应用逆向归纳技术，首先导出 ESP（跟随器）的封闭式解。然后，为了解决 IoTSP（领导者）的非凸优化问题，我们利用块坐标下降和凸凹过程技术设计两种划分方案（即部分调整（PA）和联合调整（JA））以找出构成当地SE的最佳能源价格和服务时间。数值结果表明，通过联合优化物联网设备的能源交易和时间分配，与传统传输方法相比，可以实现IoTSP利润的显着提高（高达38.7倍）。 ESP 和 IoTSP 的利润以及 PA/JA 方案的复杂性之间的不同权衡也可以进行数值调整。模拟还表明，当每传输比特的收益超过给定阈值时，获得的局部 SE 接近最优社会福利。