面向无源感知网络的并发后向散射技术研究

Backscatter provides the benefits of energy harvesting and low-power communication, making it attractive to a broad class of applications. These applications, such as warehouse inventories, supply chain management, and industry surveillance, involve large volumes of data carried by a large number of deployed backscatter nodes (i.e., the tags). Therefore, how to fully utilize the channels and enhance network throughput, turns to be a crucial problem in the relevant area. This project aims to impulse the transmission efficiency of backscatter system by enabling parallel transmission from multiple tags. Specifically, we try to make parallel transmission reliable and efficient by making the following contributions: First, we find and solve the superclustering problem, enabling reliable signal clustering under low SNR scenarios; Second, we propose to exploit the state transition pattern of the signal, instead of the IQ or time domain feature of the signal, to accurately identify the combined state of each signal cluster although the signal is highly dynamic and irregular; At last, we try to push through the limitation of the tags’ transmission power and the reader’s sampling rate, enabling parallel transmission with high degree of parallelism by exploiting the channel diversity of the backscatter tags.

无源感知网络在近年来获得了长足发展，并应用在越来越多的场景中，如仓储管理、物流追踪、工业自动化等等。然而，研究领域的现状是，无源感知网络技术仍面临若干关键瓶颈问题，其中关键瓶颈之一是，当前无源感知网络的通信协议无法保证数据收集的高效性及可靠性。因此，探究如何提高无源感知网络传输效率，是推动我国物联网产业发展、抢占物联网技术国际制高点的需要。对此，本项目拟就无源感知网络并发解码技术展开研究，实现适用于超低功耗低代价无源感知设备的高可靠并发传输。具体而言，本项目首先拟解决低信噪比条件下的信号状态分类问题，为可靠并发解码提供保障。进一步地，本项目计划利用碰撞信号在各组合状态之间的转移规律，而非信号本身特征，实现硬件资源受限条件下的高可靠性信号状态识别。最后，本项目拟克服信号能量及接收端采样率的限制，利用频率多样性特征实现基于多频段信道技术的高吞吐并发传输。

随着无源终端设备持续增加以及行业应用的不断深入，大规模无源通信及感知系统日渐普及。然而现有的无源通信及感知设备接入信道须采用时分复用的方法，导致其信道资源利用率低，网络吞吐率非常有限。基于以上问题，本项目研究并提出了一系列适用于超低代价无源设备的高可靠并发传输技术，实现了8个无源设备的并发传输，将无源感知网络吞吐提高近20倍。具体研究内容包括：.1. 依赖信号转移概率模型实现非同步并发技术.2. 依赖信号时空变化规律实现弱信号并发技术.3. 依赖信号频率多样特征实现大规模并发技术.除此之外，本项目还进一步将研究问题由并发传输扩展到并发感知，构建并发信道估计模型及全息感知模型，并在此基础上提出一系列多维度、细粒度、量化感知技术。