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Recent advancements in low power micro sensors and wireless network technology have enabled a host of new sensor network applications. One such application is collaborative geolocation using time difference of arrival measurements from a wireless sensor network consisting of mobile ground or airborne sensor nodes. This paper introduces a two-stage geolocation scheme that begins in an optimal bearing estimate formation and then reconfigures to a formation that yields an optimal position estimate. Using optimal sensor formations for bearing and position estimates, enables a network to obtain an optimal estimate of a target emitter's position. Through simulation the performance of such a scheme is analyzed and compared to that of a random fixed array. Its implementation on an airborne quadrotor network is also explored and is shown to be viable despite the network's unsteady node station keeping. [ABSTRACT FROM PUBLISHER]

Source localization and tracking of a Cognitive Radio (CR) is a significant challenge because of the dynamic opportunistic behavior of the radio across the spatial, frequency, and temporal domains. For any localization or tracking scheme to be effective, it must be able to adapt as a CR adapts to its surroundings. The extended semi range-based (ESRB) localization scheme was proposed as a solution to the aforementioned problem, but resulted in considerable communication overhead and storage requirements within the wireless sensor network (WSN) as well as poor reliability due to frequent divergence of the non-linear least squares method (NLSM) in the localization process. Furthermore, tracking a mobile CR was accomplished in a brute force manner by repeating the same positioning technique without taking advantage of prior position estimates. In this paper, the ESRB localization scheme is modified to incorporate the Kalman filter as a recursive estimator to reduce the burden placed on the WSN and integrate an efficient means to estimate the position and velocity of a mobile CR over time. The proposed modification is modeled in the MATLAB programming language, and its efficacy is demonstrated through simulation. It is shown that the Kalman filter is an appropriate recursive estimator for use in the ESRB localization scheme, while accounting for both frequency and spatial mobility inherent in the CR environment. [ABSTRACT FROM PUBLISHER]

Communications networks are valuable in proportion to the trustworthy information they carry. Network security policies are designed to classify nodes as trustworthy or not with some probability of error when the true status of each node is unknown. By making an analogy with the binary symmetric channel model, properties of networks with optimal security policies are derived. Additive and multiplicative utility models with and without aversion to misclassification risk are considered. [ABSTRACT FROM PUBLISHER]

A novel scheme for mobile subscriber positioning is proposed based on the hidden-Markov model (HMM) and the cell-ID maximum-likelihood database correlation method also known as fingerprinting. Using a simulated channel environment, based on the Clearwire deployment of WiMAX base stations in San Jose, CA, we show that matching the right configuration of the model to the deployment environment can realize significant gains in performance. The proposed scheme balances the scalability inherent in hidden-Markov-based motion models deployed in large areas of interest against the existing channel conditions and computational capability. By utilizing a simulated channel this paper demonstrates the effect of base station deployment and shadowing on the fingerprint-based HMM motion model. Further, the benefits gained through scaling the HMM are explored. [ABSTRACT FROM PUBLISHER]

Spatiotemporal clustering is the process of grouping objects based on both their spatial and temporal similarity. This approach is useful when considering the distance between objects and how that distance changes through time. Spatiotemporal clustering analysis is applied to the maritime domain in this paper, specifically to a defined area of water, during a period of time, in order to gain behavioral knowledge of vessel interactions and provide the opportunity to screen such interactions for further investigation. The proposed spatiotemporal clustering algorithm spatially clusters vessels in the water space using k-means clustering analysis, kinematically refines the clusters based on the similarity of vessel headings, speeds and the distance between them, and temporally analyzes the continuity of membership of the kinematic clusters through time to determine which clusters are moving. The algorithm is implemented in the MATLAB programming environment, verified with a synthetic data scenario, and validated with two real-world datasets. [ABSTRACT FROM PUBLISHER]

Wireless network security is a daunting challenge as researchers analyze the vulnerabilities of wireless medium access control schemes such as IEEE 802.11, Bluetooth, and IEEE 802.16. While these wireless protocols employ traditional contention and non-contention approaches, recent work has identified the delay and throughput performance advantages of a flow-specific medium access hybrid solution for wireless networks such as the traffic-adaptive Cooperative Wireless Sensor Medium Access Control (CWS-MAC) protocol. Accordingly, this paper addresses the security of wireless networks employing these hybrid, flow-specific schemes by analyzing the vulnerabilities in traffic-adaptive CWS-MAC, many of which are applicable to hybrid medium access schemes in general. Critical vulnerabilities are identified that expose the protocol to denial of service, energy exhaustion and "greedy" attacks. The effect of attacks exploiting these vulnerabilities are shown to include decreased throughput and increased delay in both the contention and non-contention modes as well as increased per node energy consumption. [ABSTRACT FROM PUBLISHER]

Timing adjusts, used for synchronization in control signaling in IEEE 802.16-2009 mobile WiMax systems, can be used to geolocate a mobile subscriber. From Time of Arrival (TOA) and Time Difference of Arrival (TDOA) calculations, two key observations are made. First, geolocation error occurs when calculating in a two-dimensional plane. Second, TDOA calculations can eliminate the initial bias of a measured timing adjust and thereby allow geolocation calculations with less knowledge of the system. Through simulation, the three-dimensional TOA and TDOA methods are shown to outperform the corresponding two-dimensional methods. Experimentation with an Alcatel-Lucent 802.16e-2005 OFDMA-based system validates the accuracy of the three-dimensional geolocation method with an average geolocation error of 23 meters compared to 87 meters for the two-dimensional approach. [ABSTRACT FROM PUBLISHER]

This paper proposes a scheme for identification and classification of Orthogonal Frequency Division Multiple Access (OFDMA) signals. Specifically, the cyclostationary pilot signature of an IEEE 802.16e standard compliant waveform is investigated. The proposed scheme performs waveform identification through a preamble cross-correlation technique. Classification is achieved through the use of a pilot cross-correlation technique in combination with cyclostationary feature extraction in order to determine the cyclic prefix of the IEEE 802.16e waveform. Similar methods are then used for determining other OFDMA waveform parameters, such as the FFT size, Segment number and IDcell. MATLAB simulation results validate the preamble cross-correlation and pilot cross-correlation techniques as effective methods of signal identification and classification, respectively. [ABSTRACT FROM PUBLISHER]

In this paper, the base station identification and timing adjust measurements are used to geolocate mobile subscribers in a WiMAX network. The uplink and downlink subframes of the physical layer and management messages of the medium access control layer are examined to extract the necessary data for geolocation. Using a hidden Markov model [1] based algorithm to estimate the track of the mobile subscriber, we demonstrate that the position error can be further reduced by incorporating timing adjust measurements. Simulation results of the proposed scheme are included to demonstrate the effectiveness of the combined use of base station ID and timing adjust measurements. [ABSTRACT FROM PUBLISHER]

Cognitive radio (CR) presents a unique challenge to source localization in that the radio has the ability to adapt to the environment, thus rendering current localization techniques ineffective due to a shifting combination of spatial, frequency, and temporal parameters. For any localization scheme to be effective, it must be able to adapt over time as a CR adapts to its surroundings. In this paper an extended semi range-based localization (ESRB) scheme is proposed to accomplish this task. The proposed scheme estimates the position of a CR using the collaborative spectrum sensing results of a wireless radio frequency sensor network (WSN) in a CR environment. The central idea behind the proposed scheme is to exploit the relationships between spatial, frequency, and temporal parameters of the environment to solve for the position of the CR. The proposed scheme is modeled in the MATLAB programming language, and its efficacy is demonstrated through simulation. It is shown that over time the proposed scheme is capable of estimating the frequency band of operation and the location of a CR, and is thus capable of accounting for both frequency and spatial mobility inherent in the CR environment. [ABSTRACT FROM PUBLISHER]

We present a scheme for identifying and selecting high performing channels in a multi-channel wireless network through the application of a state based approach. The proposed scheme can increase throughput and reduce delay; however a significant challenge is node coordination. In dedicated control channel schemes, data channels are selected based upon channel agreement between nodes. One widely implemented channel selection scheme is random selection which can lead to suboptimal network performance when one or more data channels are disadvantaged. Our proposed channel selection scheme is shown to overcome the inefficiency of random selection. We develop a theoretical performance model of our state based selection scheme and compare it against random selection. We then present simulation results to demonstrate a significant reduction in transmission errors by state based over random selection. [ABSTRACT FROM PUBLISHER]

Introduction to Wireless Networks Minitrack [ABSTRACT FROM PUBLISHER]