Distributed Space-Time Communication For Wireless Sensor Networks

无线传感器网络具有广泛的应用前景，包括环境监测、家庭和工厂自动化以及国土安全。 本研究解决了传感器网络的有效数据收集问题，这是低成本传感器节点大规模部署的根本瓶颈之一。 两个关键的困难是规模（如何管理大量相对不复杂的节点）和能源（通信是能源密集型的，但传感器节点必须靠电池或从环境中收集能量运行数月或数年）。本研究有两个互补的研究方向，都是研究从传感器网络收集数据的新技术，利用传感器节点在空间的自然分布。 第一种称为virtualradar，通过将复杂性转移到复杂的数据收集节点，可以部署非常简单的传感器节点，这些节点不需要联网或定位功能。 第二种方法需要更复杂的节点，并通过相邻（单天线）传感器节点之间的智能协调来获得多天线传输功能，从而提高能效和范围。在第一个推力中，称为虚拟雷达，具有活动报告的传感器节点以电子方式反射由“驾车”或“飞越”收集器节点发送的信标，从而创建类似雷达的几何形状。 收集器采用类似于合成孔径雷达的信号处理技术来获得传感器场活动的“图像”，并研究了在收集器上利用多个天线跟踪穿过传感器场的事件。 第二个推力，称为分布式传输，涉及调查波束形成，多样性和功率增益通过相邻节点之间的协调，作为节点之间实现的同步水平的函数。 实现这种同步的方法也被认为是。

Wireless sensor networks have a large array of potential applications,including environmental monitoring, home and factory automation, andhomeland security. This research addresses efficient data collectionfrom sensor networks, which is one of the fundamental bottlenecks tolarge-scale deployment of low-cost sensor nodes. Two key difficultiesare scale (how to manage very large numbers of relativelyunsophisticated nodes) and energy (communication is energy-intensive,but sensor nodes must operate for months or years on battery, or byscavenging energy from the environment). This research has twocomplementary research thrusts, both investigating novel techniquesfor data collection from sensor networks, exploiting the naturaldistribution of sensor nodes in space. The first, termed virtualradar, enables deployment of extremely simple sensor nodes which donot need networking or position location functionality, by moving thecomplexity to a sophisticated data collection node. The secondapproach requires more sophisticated nodes, and increases energyefficiency and range by obtaining the functionality of multi-antennatransmission by intelligent coordination between neighboring(single-antenna) sensor nodes.In the first thrust, termed virtual radar, sensor nodes with activityto report electronically reflect a beacon transmitted by a"driveby" or "flyby" collector node, thuscreating a radar-like geometry. The collector employs sophisticatedsynthetic aperture radar like signal processing techniques to obtainan "image" of the activity in the sensor field.Tracking of events moving across the sensor field, and exploitingmultiple antennas at the collector, are investigated. The secondthrust, termed distributed transmission, involves investigation ofbeamforming, diversity and power gains obtained by coordinatingbetween neighboring nodes, as a function of the level ofsynchronization achieved among the nodes. Methods of achieving suchsynchronization are also considered.