1,537 research outputs found
Optimal Relay Selection with Non-negligible Probing Time
In this paper an optimal relay selection algorithm with non-negligible
probing time is proposed and analyzed for cooperative wireless networks. Relay
selection has been introduced to solve the degraded bandwidth efficiency
problem in cooperative communication. Yet complete information of relay
channels often remain unavailable for complex networks which renders the
optimal selection strategies impossible for transmission source without probing
the relay channels. Particularly when the number of relay candidate is large,
even though probing all relay channels guarantees the finding of the best
relays at any time instant, the degradation of bandwidth efficiency due to
non-negligible probing times, which was often neglected in past literature, is
also significant. In this work, a stopping rule based relay selection strategy
is determined for the source node to decide when to stop the probing process
and choose one of the probed relays to cooperate with under wireless channels'
stochastic uncertainties. This relay selection strategy is further shown to
have a simple threshold structure. At the meantime, full diversity order and
high bandwidth efficiency can be achieved simultaneously. Both analytical and
simulation results are provided to verify the claims.Comment: 8 pages. ICC 201
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
Double-Directional Information Azimuth Spectrum and Relay Network Tomography for a Decentralized Wireless Relay Network
A novel channel representation for a two-hop decentralized wireless relay
network (DWRN) is proposed, where the relays operate in a completely
distributive fashion. The modeling paradigm applies an analogous approach to
the description method for a double-directional multipath propagation channel,
and takes into account the finite system spatial resolution and the extended
relay listening/transmitting time. Specifically, the double-directional
information azimuth spectrum (IAS) is formulated to provide a compact
representation of information flows in a DWRN. The proposed channel
representation is then analyzed from a geometrically-based statistical modeling
perspective. Finally, we look into the problem of relay network tomography
(RNT), which solves an inverse problem to infer the internal structure of a
DWRN by using the instantaneous doubledirectional IAS recorded at multiple
measuring nodes exterior to the relay region
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