Resilient wireless communications using randomly deployed transceivers

存在许多新兴的无线概念和应用，其中在可变条件下部署不同大小和能力的无线电节点。此外，部署在城市中或沿着道路的无线系统数量的快速增长将产生不可预测的干扰环境。由于许多新的应用设想使用具有一个或多个天线的微型无线电设备，因此重要的是开发新的概念，以允许这种设备在广泛的条件下以合理的可靠性运行。关键是在节点中建立足够的灵活性，以便能够使其通信参数适应周围环境。 建议的研究重点是ad-hoc无线通信的四个方面。第一个方面是以现实的方式对随机部署的无线电的路径损耗和散射特性进行建模和表征。 我们计划在不同的条件下测量信道的信号强度和功率延迟曲线。 第二个方面是表征传输带宽、传播环境之间的关系。部署的距离和密度、数据传输能力和节点的生命周期。第三个方面是设计、模拟和测试新概念，使小节点能够适应其环境，以保持可靠的通信。 第四个方面是提出创新方法，以提高网络的可靠性和健康状况。 基于测量的传播建模将提供对创建无线节点的自适应结构的方法的洞察。特别是，我们的目标是研究天线和自适应滤波器的作用，以建立鲁棒性。最后，我们的目标是根据实际应用检查我们的模型，例如在监测大面积安全，安全或监测空气和水质量时遇到的条件。

There are many emerging wireless concepts and applications, where radio nodes of different sizes and capabilities are deployed under variable conditions. Also, the fast growth in the number of wireless systems deployed in a city or along a road will create an unpredictable interference environment. Since many of the new applications envisage using miniature radio devices with one or multiple antennas, it is important to develop new concepts that allow such devices to function with reasonable reliability under a wide range of conditions. The key is to build into the node enough flexibility in order to be able to adapt its communication parameters to the surrounding environment. The proposed research focuses on four aspects of ad-hoc wireless communications. The first aspect is to model and characterize the pathloss and scattering properties of randomly deployed radios in a realistic way. We plan to measure the signal strength and power delay profiles of the channels under different conditions. The second aspect is to characterize the relation between the transmission bandwidth, the propagation environment. Distance and density of deployment, data transfer capability and the life time of the node. The third aspect is to design, simulate and test new concepts that allow a small node to adapt to its environment in order to maintain reliable communications. The fourth aspect is to propose innovative methodologies to enhance the reliability of and health of the network. Measurement-based propagation modelling will provide an insight into ways to create an adaptive structure for the wireless node. In particular, we are aiming at examining the role of antennas and adaptive filters as ways to build robustness. Finally, we aim to examine our models against real-life applications such as the conditions encountered in monitoring large areas for safety, security or for monitoring the quality of air and water.