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LinearRegression Estimation of the PropagationLoss Parameters Using Mobiles ’ Measurements in Wireless Cellular Networks
"... We propose a new linearregression model for the estimation of the pathloss exponent and the parameters of the shadowing from the propagationloss data collected by the mobiles with respect to their serving base stations. The difficulty consists in deriving the parameters of the distribution of the ..."
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We propose a new linearregression model for the estimation of the pathloss exponent and the parameters of the shadowing from the propagationloss data collected by the mobiles with respect to their serving base stations. The difficulty consists in deriving the parameters of the distribution of the propagation loss with respect to an arbitrary base station from these regarding the strongest one. The proposed solution is based on a simple, explicit relation between the two distributions in
Secure Distancebased Localization in the Presence of Cheating Beacon Nodes
"... Abstract—Secure distancebased localization in the presence of cheating beacon (or anchor) nodes is an important problem in mobile wireless ad hoc and sensor networks. Despite significant research efforts in this direction, some fundamental questions still remain unaddressed: In the presence of chea ..."
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Abstract—Secure distancebased localization in the presence of cheating beacon (or anchor) nodes is an important problem in mobile wireless ad hoc and sensor networks. Despite significant research efforts in this direction, some fundamental questions still remain unaddressed: In the presence of cheating beacon nodes, what are the necessary and sufficient conditions to guarantee a bounded error during a twodimensional distancebased location estimation? Under these necessary and sufficient conditions, what class of localization algorithms can provide this error bound? In this paper, we attempt to answer these and other related questions by following a careful analytical approach. Specifically, we first show that when the number of cheating beacon nodes is greater than or equal to a given threshold, there do not exist any twodimensional distancebased localization algorithms that can guarantee a bounded error. Furthermore, when the number of cheating beacons is below this threshold, we identify a class of distancebased localization algorithms that can always guarantee a bounded localization error. Finally, we outline three novel distancebased localization algorithms that belong to this class of bounded error localization algorithms. We verify their accuracy and efficiency by means of extensive simulation experiments using both simple and practical distance estimation error models. Index Terms—Wireless networks, distancebased localization, security. 1
Path Loss Exponent Estimation in Large Wireless Networks
"... Abstract—In wireless channels, the path loss exponent (PLE) has a strong impact on the quality of the links, and hence, it needs to be accurately estimated for the efficient design and operation of wireless networks. This paper addresses the problem of PLE estimation in large wireless networks, whic ..."
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Abstract—In wireless channels, the path loss exponent (PLE) has a strong impact on the quality of the links, and hence, it needs to be accurately estimated for the efficient design and operation of wireless networks. This paper addresses the problem of PLE estimation in large wireless networks, which is relevant to several important issues in communications such as localization, energyefficient routing, and channel access. We consider a large ad hoc network where nodes are distributed as a homogeneous planar Poisson point process and the channels are subject to Nakagamim fading. Under these settings, we propose and study three distributed algorithms for estimating the PLE at each node, which explicitly take into account the interference in the network. Additionally, we provide simulation results to demonstrate the performance of the algorithms and quantify the estimation errors.
Path Loss Exponent Estimation
 in Large Wireless Wetworks,” in Information Theory and Applications Workshop, 2009
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Secure Distance Indicator Leveraging Wireless Link Signatures
"... Time (RTT) are two common metrics for a wireless receiver to tell the proximity of a remote wireless transmitter. A large RSS or a small RTT normally indicates a close transmitter, and vice versa. Both metrics are effective in a benign environment. However, when the transmitter modifies the send tim ..."
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Time (RTT) are two common metrics for a wireless receiver to tell the proximity of a remote wireless transmitter. A large RSS or a small RTT normally indicates a close transmitter, and vice versa. Both metrics are effective in a benign environment. However, when the transmitter modifies the send time or transmit power to hide its real distance, they may fail to identify the actual proximity of the transmitter. In this paper, we propose a secure physical layer metric that not only reflects the distance between the transmitter and the receiver, but is difficult to manipulate. Our theoretical and experimental studies show that the proposed metric and the distance is inverse proportional, in both the ideal and practical scenarios with shadow fading and channel noise. We also create distance distribution profiles based on the proposed metric, and point out how such profiles can be used to enhance the reliability of the distance estimation. I.
Dynamic Path Loss Exponent Estimation in a Vehicular Network using Doppler Effect and Received Signal Strength
"... Abstract — Localization in Adhoc wireless sensor networks is one of the important and demanded fields in engineering research and industry. Among these networks, vehicular Adhoc network, VANET, with emerging applications like Intelligent Transport Systems is considered as the most challenging area ..."
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Abstract — Localization in Adhoc wireless sensor networks is one of the important and demanded fields in engineering research and industry. Among these networks, vehicular Adhoc network, VANET, with emerging applications like Intelligent Transport Systems is considered as the most challenging area. One of the fundamental parameters in VANET applications is the distances between the nodes which must be measured or estimated. Among the variety of radio range measurement techniques, Received Signal Strength (RSS) is very popular due to its simplicity and less cost compared to other methods like Time of Arrival (TOA), Time Difference of Arrival (TDOA), and Angel of Arrival (AOA). The main drawback of RSS based ranging is its considerable inaccuracy which is mostly originated from uncertainty of the path loss exponent which has an exponential effect on distance measurement. Without knowing the environment path loss exponent, which is a time varying parameter in the networks with mobility, RSS is useless for distance estimation. There are many approaches and techniques proposed in literature for dynamic estimation of path loss exponent within a certain environment. Most of these methods are not functional for mobile applications or their efficiency decreases dramatically with increasing the mobility of the nodes. In this paper, we propose a method for dynamic estimation of path loss exponent and distance based on Doppler Effect and RSS. Since this method is fundamentally based on Doppler Effect, it can be implemented within the networks with nodes relative mobility. The higher mobility of the nodes, the better performance of the proposed technique. Also, the proposed method is more suitable for vehicular networks in which, nodes are moving in the road constraint. The importance of this work contribution can be highlighted as the vehicles are going to be equipped with
Efficient Energy Management and Data Recovery in Sensor Networks using Latent Variables Based Tensor Factorization
"... A key factor in a successful sensor network deployment is finding a good balance between maximizing the number of measurements taken (to maintain a good sampling rate) and minimizing the overall energy consumption (to extend the network lifetime). In this work, we present a datadriven statistical m ..."
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A key factor in a successful sensor network deployment is finding a good balance between maximizing the number of measurements taken (to maintain a good sampling rate) and minimizing the overall energy consumption (to extend the network lifetime). In this work, we present a datadriven statistical model to optimize this tradeoff. Our approach takes advantage of the multivariate nature of the data collected by a heterogeneous sensor network to learn spatiotemporal patterns. These patterns enable us to employ an aggressive duty cycling policy on the individual sensor nodes, thereby reducing the overall energy consumption. Our experiments with the OMNeT++ network simulator using realistic wireless channel conditions, on data collected from two realworld sensor networks, show that we can sample just 20% of the data and can reconstruct the remaining 80 % of the data with less than 9 % mean error, outperforming similar techniques such is distributed compressive sampling. In addition, energy savings ranging up to 76%, depending on the sampling rate and the hardware configuration of the node.
SelfEstimation of PathLoss Exponent in Wireless Networks and Applications
"... Abstract—The pathloss exponent (PLE) is one of the most crucial parameters in wireless communications to characterize the propagation of fading channels. It is currently adopted for many different kinds of wireless network problems such as power consumption issues, modeling the communication enviro ..."
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Abstract—The pathloss exponent (PLE) is one of the most crucial parameters in wireless communications to characterize the propagation of fading channels. It is currently adopted for many different kinds of wireless network problems such as power consumption issues, modeling the communication environment, and received signal strength (RSS)based localization. PLE estimation is thus of great use to assist wireless networking. However, a majority of methods to estimate the PLE requires either some particular information of the wireless network, which might be unknown, or some external auxiliary devices, such as anchor nodes or the global positioning system (GPS). Moreover, this external information might sometimes be unreliable, spoofed or difficult to obtain. Therefore, a selfestimator for the PLE, which is able to work independently, becomes an urgent demand to robustly and securely get a grip on the PLE for various wireless
Phase Transition Width of Connectivity of Wireless Multihop Networks in Shadowing Environment
"... Abstract—In this paper, we study the wellknown phase transition behavior of connectivity in a wireless multihop network, but, in contrast to other studies, in a shadowing environment. We consider that a total of n nodes are randomly, independently and uniformly distributed on a unit square in < ..."
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Abstract—In this paper, we study the wellknown phase transition behavior of connectivity in a wireless multihop network, but, in contrast to other studies, in a shadowing environment. We consider that a total of n nodes are randomly, independently and uniformly distributed on a unit square in <2, each node has a uniform transmission power and any two nodes are directly connected if and only if the power received by one node from the other node, as determined by the lognormal shadowing model, is larger than or equal to a given threshold. We extend the results obtained under the unit disk communication model in previous work to the more realistic lognormal shadowing model, and derive an analytical formula for the phase transition width of connectivity for large n. We also demonstrate how our results can be extended to higher dimensional networks and to other channel models. I.