The broadcast nature of a wireless link provides a natural eavesdropping and intervention capability to an adversary. Thus, securing a wireless link is essential to the security of a wireless network, and key generation algorithms are necessary for securing wireless links. However, traditional key agreement algorithms can be very costly in many settings, e.g. in wireless ad-hoc networks, since they consume scarce resources such as bandwidth and battery power.Traditional key agreement algorithms are not suitable for wireless ad-hoc networks since they consume scarce resources such as bandwidth and battery power. This paper presents a novel approach that couples the physical layer characteristics of wireless networks with key generation algorithms. It is based on the wireless communication phenomenon known as the principle of reciprocity which states that in the absence of interference both transmitter and receiver experience the same signal envelope. The key-observation here is that the signal envelope information can provide to the two transceivers two correlated random sources that provide sufficient amounts of entropy which can be used to extract a cryptographic key. In contrast, it is virtually impossible for a third party, which is not located at one of the transceiver's position, to obtain or * This work was done in part while the author was with Rensselaer Polytechnic Institute.Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. predict the exact envelope; thus retrieve the key. Since in the presence of interference strict reciprocity property can not be maintained; our methodology is based on detecting deep fades to extract correlated bitstrings. In particular, we show how a pair of transceivers can reconcile such bitstrings and finally flatten their distribution to reach key agreement. In our constructions we use cryptographic tools related to randomness extraction and information reconciliation. We introduce "secure fuzzy information reconciliators" a tool that enables us to describe robust key generation systems in our setting. Finally we provide a computational study that presents a simulation of a wireless channel that demonstrates the feasibility of our approach and justifies the assumptions made in our analysis.

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The capacity of wireless ad hoc networks is constrained by the interference caused by the neighboring nodes. Gupta and Kumar have shown that the throughput for such networks is only ( W √ n ) bits per second per node in a unit area domain when omnidirectional antennas are used [1]. In this paper we investigate the capacity of ad hoc wireless networks using directional antennas. Using directional antennas reduces the interference area caused by each node, thus increases the capacity of the network. We will give an expression for the capacity gain and we argue that in the limit, when the beam-width goes to zero the wireless network behaves like the wired network. In our analysis we consider both arbitrary networks and random networks where nodes are assumed to be static. We have also analyzed hybrid beamform patterns that are a mix of omnidirectional/directional and a better model of real directional antennas. Simulations are conducted for validation of our analytical results.

In this paper, we introduce for the first time particle filtering for an exponential family of densities. We prove that under certain conditions the approximated conditional density of the state converges to the true conditional density. In the realistic setting where the conditional density does not lie in an exponential family but stays close to it, we show that under certain assumptions the error of the estimate given by an approximate nonlinear filter (which we call the projection particle filter), is bounded. We use projection particle filtering in state estimation for a combination of inertial navigation system (INS) and global positioning system (GPS), referred to as integrated INS/GPS. We illustrate via numerical experiments that projection particle filtering outperforms regular particle filtering in navigation performance, and extended Kalman filter as well when satellite loss-of-lock occurs.

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In this paper we present a change detection method for nonlinear stochastic systems based on Projection Particle Filtering. The statistic for this method is chosen in such a way that it can be calculated recursively while the computational complexity of the method remains constant with respect to time. We present some simulation results that show the advantages of this method compared to linearization techniques.

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