Product Multicommodity Flow in Wireless Networks

We provide a tight approximate characterization of the $n$-dimensional product multicommodity flow (PMF) region for a wireless network of $n$ nodes. Separate characterizations in terms of the spectral properties of appropriate network graphs are obtained in both an information theoretic sense and for a combinatorial interference model (e.g., Protocol model). These provide an inner approximation to the $n^2$ dimensional capacity region. These results answer the following questions which arise naturally from previous work: (a) What is the significance of $1/\sqrt{n}$ in the scaling laws for the Protocol interference model obtained by Gupta and Kumar (2000)? (b) Can we obtain a tight approximation to the "maximum supportable flow" for node distributions more general than the geometric random distribution, traffic models other than randomly chosen source-destination pairs, and under very general assumptions on the channel fading model? We first establish that the random source-destination model is essentially a one-dimensional approximation to the capacity region, and a special case of product multi-commodity flow. Building on previous results, for a combinatorial interference model given by a network and a conflict graph, we relate the product multicommodity flow to the spectral properties of the underlying graphs resulting in computational upper and lower bounds. For the more interesting random fading model with additive white Gaussian noise (AWGN), we show that the scaling laws for PMF can again be tightly characterized by the spectral properties of appropriately defined graphs. As an implication, we obtain computationally efficient upper and lower bounds on the PMF for any wireless network with a guaranteed approximation factor.Comment: Revised version of "Capacity-Delay Scaling in Arbitrary Wireless Networks" submitted to the IEEE Transactions on Information Theory. Part of this work appeared in the Allerton Conference on Communication, Control, and Computing, Monticello, IL, 2005, and the Internation Symposium on Information Theory (ISIT), 200

Lecture Notes on Network Information Theory

These lecture notes have been converted to a book titled Network Information Theory published recently by Cambridge University Press. This book provides a significantly expanded exposition of the material in the lecture notes as well as problems and bibliographic notes at the end of each chapter. The authors are currently preparing a set of slides based on the book that will be posted in the second half of 2012. More information about the book can be found at http://www.cambridge.org/9781107008731/. The previous (and obsolete) version of the lecture notes can be found at http://arxiv.org/abs/1001.3404v4/

Robust minimum energy wireless routing for underwater acoustic communication networks

Marine robots are an increasingly attractive means for observing and monitoring the ocean, but underwater acoustic communications remain a major challenge. The channel exhibits long delay spreads with frequency-dependent attenuation; moreover, it is time-varying. We consider the minimum energy wireless transmission problem [MET], augmented by the practical condition that constraints on link power must be satisfied in probability. For this, we formulate the robust counterpart of the multicommodity mixed-integer linear programming (MILP) model from Haugland and Yuan [1], and derive scaled power levels that account for uncertainty. Our main result is that the deterministic formulation with these scaled power levels recovers exactly the optimal robust solution in the absence of correlations, and therefore allows for efficient solution via MILP. This approach achieves significant power improvements over heuristics, and naturally lends itself to vehicle networks.United States. Office of Naval Research (Grant N00014-09-1-0700

Scalable System Design for Covert MIMO Communications

In modern communication systems, bandwidth is a limited commodity. Bandwidth efficient systems are needed to meet the demands of the ever-increasing amount of data that users share. Of particular interest is the U.S. Military, where high-resolution pictures and video are used and shared. In these environments, covert communications are necessary while still providing high data rates. The promise of multi-antenna systems providing higher data rates has been shown on a small scale, but limitations in hardware prevent large systems from being implemented

Sub-Nanosecond Time of Flight on Commercial Wi-Fi Cards

Time-of-flight, i.e., the time incurred by a signal to travel from transmitter to receiver, is perhaps the most intuitive way to measure distances using wireless signals. It is used in major positioning systems such as GPS, RADAR, and SONAR. However, attempts at using time-of-flight for indoor localization have failed to deliver acceptable accuracy due to fundamental limitations in measuring time on Wi-Fi and other RF consumer technologies. While the research community has developed alternatives for RF-based indoor localization that do not require time-of-flight, those approaches have their own limitations that hamper their use in practice. In particular, many existing approaches need receivers with large antenna arrays while commercial Wi-Fi nodes have two or three antennas. Other systems require fingerprinting the environment to create signal maps. More fundamentally, none of these methods support indoor positioning between a pair of Wi-Fi devices without~third~party~support. In this paper, we present a set of algorithms that measure the time-of-flight to sub-nanosecond accuracy on commercial Wi-Fi cards. We implement these algorithms and demonstrate a system that achieves accurate device-to-device localization, i.e. enables a pair of Wi-Fi devices to locate each other without any support from the infrastructure, not even the location of the access points.Comment: 14 page