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Optimization of Mixed Energy Supply of IoT Network Based on Matching Game and Convex Optimization

机译:基于匹配游戏和凸优化的IOT网络混合能源优化

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摘要

The interaction capability provided by the Internet of Things (IoT) significantly increases communication between human and machine, changing our lives gradually. However, the abundant constructions of 5G small base stations (SBSs) and large-scaled access of IoT terminal equipment (TE) will surely cause a dramatic increase in energy expense costs of a wireless communication system. In this study, we designed a bilateral random model of TE allocation and energy decisions in IoT, and proposed a mixed energy supply algorithm based on a matching game and convex optimization to minimize the energy expense cost of the wireless communication system in IoT. This study divided the problem of minimizing energy expense cost of the system into two steps. First, the random allocation problem of TEs in IoT was modeled to a matching game problem. This step is to obtain the TE matching scheme that minimizes the energy consumption of the whole system on the basis of guaranteeing the quality of service of TEs. Second, the energy decision problem of SBS was modeled into a convex optimization problem. The energy purchase scheme of SBSs with the minimum energy expense cost of the system was obtained by solving the optimal solution of the convex optimization. According to the simulation results, the proposed mixed energy supply scheme can decrease the energy expense cost of the system effectively.
机译:事物互联网(物联网)提供的互动能力显着提高了人与机器之间的沟通,逐渐改变了我们的生活。然而,5G小型基站(SBSS)的丰富结构和IOT终端设备(TE)的大规模访问肯定会导致无线通信系统的能量费用成本的显着增加。在本研究中,我们设计了IOT中TE分配和能量决策的双边随机模型,并提出了一种基于匹配游戏和凸优化的混合能量供应算法,以最小化IOT中无线通信系统的能量费用成本。本研究将最小化系统的能量费用成本最小化为两个步骤。首先,IOT中TES的随机分配问题被建模为匹配的游戏问题。该步骤是获得TE匹配方案,其在保证TES的服务质量的基础上最小化整个系统的能量消耗。其次,SBS的能量决策问题被建模为凸优化问题。通过求解凸优化的最佳解决方案,获得了系统的最小能耗成本的SBS的能量采购方案。根据仿真结果,所提出的混合能量供应方案可以有效地降低系统的能量费用成本。

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