基于加权效用函数的LoRa扩频因子和码率分配
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1.中国地质大学(武汉)自动化学院 武汉 430074; 2.中山智联未来科技有限公司 中山 528437

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TN911

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湖北省自然科学基金(2022CFB269)、中山市科技计划项目(2019AG032)资助


Weighted utility function based LoRa spreading factor and coding rate allocation
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1.School of Automation, China University of Geosciences,Wuhan 430074, China; 2.Zhongshan Zhilian Future Technology Co., Ltd.,Zhongshan 528437, China

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    摘要:

    针对大规模LoRa网络数据包到达率下降、能耗急剧增加的问题,提出了基于加权效用函数的LoRa扩频因子和码率分配方法。首先,建立扩频因子和码率对数据包到达率和能耗的耦合影响关系;然后,基于赏罚机制建立数据包到达率和能耗的效用函数,并以它们的加权值为目标函数,利用贪心算法进行扩频因子和码率联合分配;最后,通过遍历搜索的方法确定最优的权重系数。仿真结果表明,相比目前最新的CA-ADR算法,所提算法的网络平均数据包到达率提高了21.2%,网络平均能效提高165%。本文算法有效提高了LoRa网络的通信可靠性和终端设备的生命周期,在智慧城市、智慧农业等众多场景具有较高的应用价值。

    Abstract:

    Aiming at the problem of declining packet delivery rate (PDR) and sharp increase in energy consumption of large-scale LoRa networks, a LoRa spreading factor (SF) and coding rate (CR) allocation method based on weighted utility function is proposed. Firstly, the coupling influence relationship between SF and CR on PDR and energy consumption is established. Then, the utility functions of PDR and energy consumption are established based on the reward and punishment mechanism, and their weighted values are taken as the objective function, and the greedy algorithm is used to jointly allocate the SF and CR. Finally, the optimal weight coefficient is determined by traversing the search. The simulation results show that compared with the latest CA-ADR algorithm, the proposed algorithm obtains a 21.2% increasment in terms of the average PDR, and a 165% increasement of the average energy efficiency. The algorithm in this paper effectively improves the communication reliability and life cycle of terminal devices in LoRa networks, and has high application value in many scenarios such as smart cities and smart agriculture.

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谢桂辉,肖华煦,王景双,胡轶斯.基于加权效用函数的LoRa扩频因子和码率分配[J].电子测量技术,2023,46(20):74-80

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  • 在线发布日期: 2024-01-23
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