The emerging internet of things (IoT) paradigm is predicted to support extremely large networks with a massive number of devices. Given the importance that IoT device are expected to play in the future communication infrastructure, it is important to understand the fundamental limits of performance of such large networks. Classically the performance limits of communications networks are studied by using a framework of information theory -- a science put forth by the pioneering engineer and scientist Claude Shannon. The goal of this research is to expand the set of tools needed for the analysis of future communication networks. Specifically, the aim is to bring necessary tools from estimation theory---a branch of statistics dealing with the recovery of noisy data. The proposed work will advance knowledge by developing a unified view of communication networks through the lens of information and estimation theories. In summary, the successful completion of the project is expected to contribute new mathematical and engineering tools, fundamentally new perspectives and models, in order to enable efficient design of the next generation of communication infrastructure.

A specific goal of this research is to study information flow over large networks by using a network transform that maps a problem of information flow over an arbitrary network to a well-structured estimation theoretic problem. In other words, instead of analyzing the problem in the classical information theoretic domain, the proposed transform offers a new estimation theoretic domain for analyzing performance of communication networks. The key attractive feature of the proposed network transform is that the underlying estimation theoretic optimization problem is a tractable one. By providing new insights and tools for studying optimal information flow over the networks via estimation theoretic techniques, this research has the potential not only to advance theory but also to improve latency, energy efficiency and robustness of emerging IoT applications. This project is a collaborative effort between researchers in the US and Israel, with funding for Israeli researchers provided by the Bi-National Science Foundation (BSF).

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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Princeton University
United States
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