无线体域网高能效通信理论研究

Wireless body area network (WBAN) worked as the basic unit for vital life signal sensing and transmission for healthcare, and the energy consumption has been considered as the biggest challenges for long-term monitoring. Because of properties of medical traffic diversity, service differentiation, and environmental dynamics, the concerns for energy consumption will be aggregated if the traditional communication techniques are still applied to the wireless body area network. On the other hand, due to the consideration of low power radio, the change of body posture can easily interfere with the communication link of wireless body area network. However, the traditional power control strategies are developed on the stable state and large scale environment, while lack of solutions in a dynamic and micro-scale environment. According to the need of green communication in the future, we first present the typical medical service behavior model and the index of medical quality of service requirements; Secondly, according to the medical traffic diversity and service difference, the key theories such as the system level optimization of energy efficiency, resource allocation and adaptive service are investigated by the combination with the specific QoS quantitative index. As for the dynamics of wireless body area network environment, we also pursue the multiple-nodes data fusion, and the context-aware dynamic power control strategies. This project would provide theoretical guidance for the widely application and standardization of internet of things for healthcare.

无线体域网作为健康物联网生命体征感知和传递的基础单元，在长期工作中能耗一直是最大的挑战。由于无线体域网具有医疗业务多样性、服务差异化、环境动态性等特点，沿用传统固定通信模式会使系统能耗浪费增大；另一方面，由于射频信号低功耗、低辐射的考虑，人体姿态改变易使无线体域网通信链路受干扰，而传统的功率控制协议都是在稳态和大尺度环境下建立的，缺乏在动态、微尺度环境下方案的研究。针对未来绿色通信的需求，我们首先对典型医疗业务进行服务质量QoS的抽象化感知，给出典型业务的行为模型与通信QoS指标要求；其次针对医疗业务的多样性和服务的差异性，结合特定的QoS量化指标，研究系统级能效多变量优化、资源配置与适度服务等关键理论；针对通信环境的动态性，研究多节点数据融合，提供情境感知的轻量级动态功率控制技术。本课将为更具医疗专业性、通信复杂性和能耗挑战性的健康物联网广泛应用及标准化提供理论指导。

本项目在基于体域网高能效通信理论方面开展了深入的研究。首先，在无线体域网动态环境下能效优先功率控制方面，针对现有的功率控制算法在无线体域网（WBAN）剧烈动态信道环境下性能不理想这一问题,利用情境信息对通信机制进行优化。WBAN动态信道虽然震荡剧烈，但和节点的运动具有强相关性。根据这一特性提出了两种算法：加速度协助的无线体域网功率控制算法（AA-TPC）和利用步伐信息的无线体域网功率控制算法（G-TPC）。两种算法都在无线体域网多传感器参数的背景下，利用情境信息有效的优化无线体域网通信能耗，给传统通信机制的研究带来了新思路。其次在无线体域网业务感知的能效优化与适度服务方面，根据短距离无线通信的通用架构建立了准确、完善的系统级能效模型。最后在无线体域网业务特征感知与通信需求认知方面，研究利用智能手机内置传感器进行人体运动状态识别，实现运动状态及运动量的连续监测，为业务特征感知提供情境信息。并且在此基础上提出了一种融合心电监测传感器和智能手机的低功耗情境心电感知系统，以提高心电分析的准确性，并有利于评估用户异常心电情况及心血管疾病风险。相关研究共产生了11篇SCI论文和8篇会议论文，2项标准提案，申请3项发明专利(一项PCT国际专利)。