9,805 research outputs found
Decentralized sequential change detection using physical layer fusion
The problem of decentralized sequential detection with conditionally
independent observations is studied. The sensors form a star topology with a
central node called fusion center as the hub. The sensors make noisy
observations of a parameter that changes from an initial state to a final state
at a random time where the random change time has a geometric distribution. The
sensors amplify and forward the observations over a wireless Gaussian multiple
access channel and operate under either a power constraint or an energy
constraint. The optimal transmission strategy at each stage is shown to be the
one that maximizes a certain Ali-Silvey distance between the distributions for
the hypotheses before and after the change. Simulations demonstrate that the
proposed analog technique has lower detection delays when compared with
existing schemes. Simulations further demonstrate that the energy-constrained
formulation enables better use of the total available energy than the
power-constrained formulation in the change detection problem.Comment: 10 pages, two-column, 10 figures, revised based on feedback from
reviewers, accepted for publication in IEEE Trans. on Wireless Communication
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
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