CIF:Small: Collaborative Research: Minimum Energy Communications in Wireless Networks

本项目旨在回答无线网络中的一个基本问题：通过无线网络传输一位信息所需的能量是多少？还有一个相关的问题：如何才能设计出接近这一极限的实用网络？这样做的动机是节约能源。显然，目前人们对节能有着浓厚的兴趣。目前，据估计，消费电子产品占美国居民总用电量的11%。虽然这并不是全部用于通信，因为大多数设备都具有无线功能，但无线通信可能会占到能源消耗的很大一部分。显然，如果这种能源消耗能够减半，节省的金额就会很大。事实上，初步结果表明，通过优化信令，无线通信的能耗可以降低50%以上。众所周知，很少有网络能够找到准确的香农容量。因此，这项研究以不同的方式探讨了这个问题的理论部分。对于某些网络，即使找不到准确的容量，也可以找到每比特的最小能量。当不能找到精确的每比特最小能量时，以在某一类网络上普遍存在的特定分贝内的数字的形式寻找每比特最小能量的近似值。这项研究的一个关键部分将是研究具有相关信息和失真的网络。联合信源-信道编码可以降低能量消耗，而不是单独的方法所能提供的。理论方法将与实际的编码方法相结合。

This project aims to answer a fundamental question in wireless networking: what is the energy needed to transmit one bit of information over a wireless network? And the related question: how can practical networks be designed to come close to this limit? The motivation is to save energy. It is evident that there is a strong current interest in energy conservation. Currently it is estimated that consumer electronics account for 11% of total residential electricity consumption in the US. While this is not all used on communications, as most devices have wireless capability, wireless communications could account for a significant part of this energy consumption. Clearly, if this energy consumption can be cut in half, the saving is significant. In fact, preliminary results show that by optimizing the signaling, energy consumption in wireless communications can be reduced much more than 50%.As is well known, there are few networks where the exact Shannon capacity has been found. The research therefore approaches the theoretical part of this problem in different ways. For some networks, the minimum energy per bit can be found even if the exact capacity cannot be found. When the exact minimum energy per bit cannot be found, approximations to the minimum energy per bit are sought in the form of a figure within a certain number of dB that is universal over a certain class of networks. A key part of the research will be to look at networks with correlated information and distortion. Joint source-channel coding can reduce the energy consumption beyond what a separate approach can provide. The theoretical approach will be combined with practical coding methods.