3,927 research outputs found
Dead Reckoning Localization Technique for Mobile Wireless Sensor Networks
Localization in wireless sensor networks not only provides a node with its
geographical location but also a basic requirement for other applications such
as geographical routing. Although a rich literature is available for
localization in static WSN, not enough work is done for mobile WSNs, owing to
the complexity due to node mobility. Most of the existing techniques for
localization in mobile WSNs uses Monte-Carlo localization, which is not only
time-consuming but also memory intensive. They, consider either the unknown
nodes or anchor nodes to be static. In this paper, we propose a technique
called Dead Reckoning Localization for mobile WSNs. In the proposed technique
all nodes (unknown nodes as well as anchor nodes) are mobile. Localization in
DRLMSN is done at discrete time intervals called checkpoints. Unknown nodes are
localized for the first time using three anchor nodes. For their subsequent
localizations, only two anchor nodes are used. The proposed technique estimates
two possible locations of a node Using Bezouts theorem. A dead reckoning
approach is used to select one of the two estimated locations. We have
evaluated DRLMSN through simulation using Castalia simulator, and is compared
with a similar technique called RSS-MCL proposed by Wang and Zhu .Comment: Journal Paper, IET Wireless Sensor Systems, 201
Dual-Branch MRC Receivers under Spatial Interference Correlation and Nakagami Fading
Despite being ubiquitous in practice, the performance of maximal-ratio
combining (MRC) in the presence of interference is not well understood. Because
the interference received at each antenna originates from the same set of
interferers, but partially de-correlates over the fading channel, it possesses
a complex correlation structure. This work develops a realistic analytic model
that accurately accounts for the interference correlation using stochastic
geometry. Modeling interference by a Poisson shot noise process with
independent Nakagami fading, we derive the link success probability for
dual-branch interference-aware MRC. Using this result, we show that the common
assumption that all receive antennas experience equal interference power
underestimates the true performance, although this gap rapidly decays with
increasing the Nakagami parameter of the interfering links. In
contrast, ignoring interference correlation leads to a highly optimistic
performance estimate for MRC, especially for large . In the low
outage probability regime, our success probability expression can be
considerably simplified. Observations following from the analysis include: (i)
for small path loss exponents, MRC and minimum mean square error combining
exhibit similar performance, and (ii) the gains of MRC over selection combining
are smaller in the interference-limited case than in the well-studied
noise-limited case.Comment: to appear in IEEE Transactions on Communication
On the Existence of an MVU Estimator for Target Localization with Censored, Noise Free Binary Detectors
The problem of target localization with censored noise free binary detectors
is considered. In this setting only the detecting sensors report their
locations to the fusion center. It is proven that if the radius of detection is
not known to the fusion center, a minimum variance unbiased (MVU) estimator
does not exist. Also it is shown that when the radius is known the center of
mass of the possible target region is the MVU estimator. In addition, a
sub-optimum estimator is introduced whose performance is close to the MVU
estimator but is preferred computationally. Furthermore, minimal sufficient
statistics have been provided, both when the detection radius is known and when
it is not. Simulations confirmed that the derived MVU estimator outperforms
several heuristic location estimators.Comment: 25 pages, 9 figure
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