Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Ultra logconcave sequences and negative dependence
Journal of Combinatorial Theory Series A
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
Latency of wireless sensor networks with uncoordinated power saving mechanisms
Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing
Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Bounds on hop distance in greedy routing approach in wireless ad hoc networks
International Journal of Wireless and Mobile Computing
On the hop count statistics for randomly deployed wireless sensor networks
International Journal of Sensor Networks
Geographic Random Forwarding (GeRaF) for Ad Hoc and Sensor Networks: Multihop Performance
IEEE Transactions on Mobile Computing
Information dissemination in large-scale wireless networks with unreliable links
Proceedings of the 4th Annual International Conference on Wireless Internet
Stochastic geometry and random graphs for the analysis and design of wireless networks
IEEE Journal on Selected Areas in Communications - Special issue on stochastic geometry and random graphs for the analysis and designof wireless networks
Bounds on the information propagation delay in interference-limited ALOHA networks
WiOPT'09 Proceedings of the 7th international conference on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks
On Multihop Distances in Wireless Sensor Networks with Random Node Locations
IEEE Transactions on Mobile Computing
Probability, Random Processes, and Ergodic Properties
Probability, Random Processes, and Ergodic Properties
Probability: Theory and Examples
Probability: Theory and Examples
Probability of k-hop connection under random connection model
IEEE Communications Letters
Stochastic Processes
ACM Transactions on Sensor Networks (TOSN)
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We consider target localization in randomly deployed multi-hop wireless sensor networks, where messages originating from a sensor node are broadcast by flooding and the node-to-node message delays are characterized by independent, exponential random variables. Using asymptotic results from first-passage percolation theory and a maximum entropy argument, we formulate a stochastic jump process to approximate the hop count of a message at distance r from the source node. The resulting marginal distribution of the process has the form of a translated Poisson distribution which characterizes observations reasonably well and whose parameters can be learnt, for example by maximum likelihood estimation. This result is important in Bayesian target localization, where mobile or stationary sinks of known position use the hop count conditioned on the Euclidean distance, to estimate the position of a sensor node or event within the network, based solely on observations of the hop count. For the target localization problem, simulation results show that the proposed model provides reasonably good performance, especially for densely connected networks.