Intelligent Sensing and Computing in Wireless Sensor Networks for Multiple Target Tracking

编号 030036705

推送时间 20221031

研究领域 森林经理 

年份 2022 

类型 期刊 

语种 英语

标题 Intelligent Sensing and Computing in Wireless Sensor Networks for Multiple Target Tracking

来源期刊 JOURNAL OF SENSORS

期 第367期

发表时间 20220618

关键词 SYSTEMS; 

摘要 With sixth generation (6G) communication technologies, target sensing can be finished in milliseconds. The mobile tracking-oriented Internet of Things (MTT-IoT) as a kind of emerging application network can detect sensor nodes and track targets within their sensing ranges cooperatively. Nevertheless, huge data processing and low latency demands put tremendous pressure on the conventional architecture where sensing data is executed in the remote cloud and the short transmission distance of 6G channels presents new challenges into the design of network topology. To cope with the above difficulties, this paper proposes a new resource allocation scheme to perform delicate node scheduling and accurate tracking in multitarget tracking mobile networks. The dynamic tracking problem is formulated as an infinite horizon Markov Decision Process (MDP), where the state space that considers energy consumption, system responding delay, and target important degree is extended. A model-free reinforcement learning is applied to obtain satisfied tracking actions by frequent iterations, in which smart agents interact with the complicated environment directly. The performance of each episode is evaluated by the action-value function in search of the optimal reward. Simulation results demonstrate that the proposed scheme shows excellent tracking performance in terms of energy cost and tracking delay.

服务人员 付贺龙

服务院士 唐守正

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