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Energy and channel transmission management algorithm for resource harvesting body area networks:

机译:资源采集人体局域网的能量和信道传输管理算法:

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In body area networks, sustainable energy supply and reliable data transmission are important to prolong the service cycle and guarantee the quality of service. In this article, we build a system model to capture the stochastic processes in body area networks, including energy harvesting process, spectrum pricing process, and data sampling process. In the system model, energy harvesting technology and cognitive radio technology are adopted to provide green energy and improve transmission environment for body area networks. Based on the proposed model, we formulate an optimization problem of system utility maximization. Since this problem is a multi-objective mixed-integer problem under multiple restrictions, we decompose the problem into several subproblems by Lyapunov optimization theory. Based on this, we design an efficient online energy and channel transmission management algorithm to solve these subproblems and achieve a close-to-optimal system utility without any priori knowledge. We analyze the optimality of proposed algorithm and derive the required battery capacity and the size of data buffer. Simulation results demonstrate the effectiveness of the proposed algorithm.
机译:在人体局域网中,可持续的能源供应和可靠的数据传输对于延长服务周期和确保服务质量至关重要。在本文中,我们建立了一个系统模型来捕获人体局域网中的随机过程,包括能量收集过程,频谱定价过程和数据采样过程。在系统模型中,采用能量收集技术和认知无线电技术来提供绿色能源并改善人体局域网的传输环境。基于提出的模型,我们提出了系统效用最大化的优化问题。由于此问题是在多个约束下的多目标混合整数问题,因此我们使用Lyapunov优化理论将其分解为几个子问题。基于此,我们设计了一种有效的在线能量和通道传输管理算法,以解决这些子问题,并在没有任何先验知识的情况下实现接近最佳的系统实用性。我们分析了所提出算法的最优性,并得出了所需的电池容量和数据缓冲区的大小。仿真结果证明了该算法的有效性。

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