III: Small: Reformulating Distributed Source Coding using Graphical Inference for Sensor Networks

传感器技术在最近几十年里有了巨大的发展。利用微米和纳米技术，现在的传感器设备可以实现极小的尺寸。廉价的传感器网络现在可以很容易地部署到条件恶劣的地区，为环境、军事和其他科学应用提供持续监测。由于大多数传感器网络用于野外或战场等难以到达的地区，对单个传感器进行定期维护是非常昂贵的，甚至是不可行的。因此，传感器的平均电池寿命本质上决定了网络本身的寿命。虽然传感器的处理功率消耗可以通过计算技术的进步来降低，但用于通信的功率消耗只能通过减少传输的净信息量来节省。因此，研究先进的信号处理技术以降低通信功率对下一代传感器网络至关重要。分布式信源编码(DSC)被认为是显著降低传感器网络通信能耗的技术。然而，目前DSC的局限性阻碍了其在传感器网络中的应用。本研究的目的是通过将下一代传感器网络的DSC重塑为图的推理问题来推进DSC的研究现状。由此产生的技术预计将大大减少通信的电力消耗，从而延长这种网络的寿命。为了实现这一目标，研究人员研究了具有两个以上终端的信源的DSC设计，具有动态变化相关的信源的自适应DSC算法，以及超越置信度传播(BP)算法的DSC的变分推理。

Sensor technology has grown tremendously in the recent decades. Using micro- and nano-technologies, sensor devices nowadays can be implemented in extremely small sizes. Networks of inexpensive sensors can now be easily deployed to areas in harsh conditions to provide continuous monitoring for environmental, military, and other scientific applications. As most sensor networks are utilized in hardly accessible areas such as a wilderness or battlefield, it is very costly or even infeasible to keep periodic maintenance of individual sensors. Therefore, the average battery life of the sensors essentially determines the life of the network itself. While the processing power consumption of a sensor can be reduced through the advance of computing technology, power consumed for communications can only be conserved by reducing the net amount of transferred information. Thus, research on advanced signal processing techniques for reducing communications power is essential for next-generation sensor networks.Distributed source coding (DSC) has been considered as the technology to drastically reduce energy consumption due to communications in sensor networks. However, current limitations of DSC prevent its adoption in sensor networks. The objective of this research is to advance the state-of-the-art of DSC for next-generation sensor networks by remodeling DSC as graphical inference problems. The resulting technologies are expected to lead to significant reduction of power consumption for communications and thus prolonged life span of such networks. To accomplish the goal, the researchers study DSC design for sources with more than two terminals, adaptive DSC algorithms for sources with dynamic varying correlation, and variational inference of DSC beyond the belief propagation (BP) algorithm.