NI-MAC: MAC Protocol Design for Neural Interfaces.

Hongbo Wu, Yukuan Jia, Sheng Zhou,Zhisheng Niu

International Conference on e-Health Networking, Applications and Services(2023)

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摘要
Neural interfaces play a crucial role in biomedical engineering since they serve as pathways of communication linking the brain and computers. Integrating wireless neural interfaces with a Media Access Control (MAC) protocol presents an efficient method for recording and analyzing neural activities simultaneously from multiple sensor nodes. However, current wireless networks, such as Wireless Sensor Networks (WSNs) and Wireless Body Area Networks (WBANs), are not directly applicable to neural interface networks, due to the high complexity and weak priority access support. This paper proposes a MAC protocol called NI-MAC that not only includes priority access but also simplifies the superframe structure and frame formats. Both random access and managed access are included in the superframe design. Analysis of transmission latency and energy consumption shows the improvement over IEEE 802.15.4 and IEEE 802.15.6. With NS3 simulator, we compare the proposed NI-MAC with existing protocols and demonstrate that: transmission latency of high-priority data can achieve 12ms, while under IEEE 802.15.4 it is 22ms; as the number of access nodes increases, energy consumption is reduced by up to 50% compared to IEEE 802.15.6.
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关键词
Medium Access Control,Medium Access Control Protocol,Energy Consumption,Wireless Networks,Sensor Networks,Biomedical Engineering,Random Access,Wireless Sensor Networks,Transmission Latency,Body Area Networks,Wireless Body Area Networks,Power Consumption,Data Transmission,Time Slot,Neural Signals,Low Energy Consumption,Random Data,Front End,Data Frame,Transmission Delay,Average Delay,Part Of Consumption,Transmission Duration,Node Length,Arrival Rate,Access Period,RF Front-end
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