Markov-Based Transmission Power Control in Wireless Body Area Network

Wenjing Guo, Mengxing Xu, Ting Lu
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Abstract

Reliability and energy consumption are the two important metrics in wireless body area network (WBAN) for medical application, and they are also the difficulties and key points in network research. In this article, we propose a new adaptive Markov-based transmission power control algorithm (MBPC) for a better compromise between energy consumption and reliability. The algorithm applies the Markov model to the link quality prediction using the grading strategy. Based on the prediction results, a new power adjustment strategy is proposed to extend the lifetime of the network while ensuring reliable transmission. In addition, we also incorporate open-loop thinking into the design of the algorithm to ensure the accuracy of the algorithm. The algorithm is simulated on the Castalia software platform. The simulation results show that the proposed algorithm has achieved good results in reliable transmission and energy consumption.
基于马尔可夫的无线体域网络发射功率控制
可靠性和能耗是医疗用无线体域网(WBAN)的两个重要指标,也是网络研究的难点和重点。在本文中,我们提出了一种新的自适应基于马尔可夫的传输功率控制算法(MBPC),以更好地平衡能量消耗和可靠性。该算法将马尔可夫模型应用于分级策略的链路质量预测。根据预测结果,提出了一种新的功率调整策略,在保证可靠传输的同时延长网络寿命。此外,我们还将开环思维融入到算法的设计中,以保证算法的准确性。该算法在Castalia软件平台上进行了仿真。仿真结果表明,该算法在可靠传输和能耗方面取得了较好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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