CIF: Small: Power Consumption in Communication

功耗是一个日益重要的社会问题。对于通信来说，随着无线网络中链路范围的不断缩小，编码和解码过程中消耗的功率成为系统架构选择中的一个重要因素。这是特别重要的设置，如无线病人监护，个人区域网络，传感器网络，等香农的经典信息理论只建立了thetreoff之间的速率和传输功率的概率为零，块长度趋于无穷大。这项研究是关于提供新的概念工具，推理的功耗在编码和解码以及。其核心思想是，在十亿晶体管芯片的时代，复杂性的适当度量标准是实现所消耗的功率。正如简化的通道模型已经实现了对纠错和传输功率的深入了解的复杂分析，本研究开发了易于分析的简化实现模型。这揭示了传输和处理能力之间相互作用的基本权衡。至关重要的是，开发的模型与大规模并行ASIC的迭代和“turbo”解码的现代方法兼容，同时也不限于目前已知的稀疏图码家族。通过开发一个统一的算法框架，这项研究使我们能够了解满足高速率，低失真，低延迟和低错误概率等性能目标的总功率成本。这反过来又导致了对如何更好地设计无线系统的理解：为电路设计师，通信理论家和网络研究人员之间的合作开辟了道路。

Power consumption is an increasingly important issue across society.For communication, as the ranges of links in wireless networkscontinue to shrink, the power consumed in the encoding and decodingbecomes a decidedly nontrivial factor in the choice of systemarchitecture. This is particularly important in settings such aswireless patient monitoring, personal area networks, sensor networks,etc. Shannon's classical information theory only established thetradeoff between rate and transmit power as the probability of errorgoes to zero and the block-length goes to infinity. This research isabout giving new conceptual tools for reasoning about the powerconsumption in encoding and decoding as well. The core idea is that inthe age of billion transistor chips, the proper metric for complexityis the power consumed by the implementation.Just as simplified channel models have enabled sophisticated analysisthat has revealed deep insights into error correction and transmitpower, this research develops simplified implementation models thatare amenable to analysis. This reveals the fundamental tradeoffsunderlying the interplay between transmission and processingpowers. Crucially, the models developed are compatible with modernapproaches to iterative and "turbo" decoding by massively parallelASICs, while also not being limited to just the currently knownfamilies of sparse-graph codes. By developing a unified mathematicalframework, this research allows us to understand the total power costof meeting performance objectives like high rate, low distortion, lowdelay and low probability of error. This in turn leads to anunderstanding of how to better engineer wireless systems as a whole:opening up avenues for collaboration between circuit designers,communication theorists, and networking researchers working at higherlayers.