近年来，无源感知技术得到了长足的发展，越来越多的传感器设备从有源走向了无源，摆脱了电池的束缚，因此迅速成为实现万物互联理念的最佳候选技术之一。本项目围绕高吞吐量移动无源网络传输协议及关键技术展开，研究大规模移动无源网络的高吞吐量链路层机制，非对称链接下的无源网络信道质量建模，以及异构无源网络媒体接入调度理论三大科学问题，解决移动无源网络在实际应用中存在的异构无源设备与单一网络结构的不匹配、大感知数据与低速无源传输的不匹配，节点动态移动特性与静态网络设置的不匹配等一系列亟待解决的矛盾。探索移动环境下高吞吐量的网络编码自适应理论，研究冲突不可见情况下的多节点聚合信道建模及信道估计关键技术，构建无载波监听下的大容量无源设备混合调度协议，搭建一个1000节点规模的面向实时动物疫情监控的移动无源网络原型系统，充分验证提出理论及关键技术的有效性和实用性，形成一系列国际领先水平的研究成果。

In recent years, backscatter sensing technologies have been well developed and have transformed more and more traditional battery-assisted sensors into battery-free sensing paradigms, becoming one of the most important techniques for Internet-of-Things. There are, however, several critical challenges brought by heterogeneous devices, big sensing data, and high mobility, for backscatter networks. The goal of this proposal is to research the fundamental theories and key technologies of high-throughput mobile backscatter networks. Specifically, first, we are going to investigate how to achieve fast bulk data transfer in mobile backscatter networks using automatic rate-adaptation. Second, we intend to examine multi-node channel modeling theories and accurate channel estimation schemes. Third, we plan to design an efficient medium access protocol without carrier sensing. Finally, we will implement a surveillance prototype of epidemic-prone infectious diseases for animal farming using mobile backscatter networks with over 1000 nodes and extensively validate our proposed solutions in real-world scenarios. We also expect to publish a number of papers in top conferences and journals.