2,426 research outputs found
Robust minimum energy wireless routing for underwater acoustic communication networks
Marine robots are an increasingly attractive means for observing and monitoring the ocean, but underwater acoustic communications remain a major challenge. The channel exhibits long delay spreads with frequency-dependent attenuation; moreover, it is time-varying. We consider the minimum energy wireless transmission problem [MET], augmented by the practical condition that constraints on link power must be satisfied in probability. For this, we formulate the robust counterpart of the multicommodity mixed-integer linear programming (MILP) model from Haugland and Yuan [1], and derive scaled power levels that account for uncertainty. Our main result is that the deterministic formulation with these scaled power levels recovers exactly the optimal robust solution in the absence of correlations, and therefore allows for efficient solution via MILP. This approach achieves significant power improvements over heuristics, and naturally lends itself to vehicle networks.United States. Office of Naval Research (Grant N00014-09-1-0700
Reconfigurable Intelligent Surfaces in Challenging Environments: Underwater, Underground, Industrial and Disaster
Reconfigurable intelligent surfaces (RISs) have been introduced to improve
the signal propagation characteristics by focusing the signal power in the
preferred direction, thus making the communication environment "smart". The
typical use cases and applications for the "smart" environment include beyond
5G communication networks, smart cities, etc. The main advantage of employing
RISs in such networks is a more efficient exploitation of spatial degrees of
freedom. This advantage manifests in better interference mitigation as well as
increased spectral and energy efficiency due to passive beam steering.
Challenging environments comprise a range of scenarios, which share the fact
that it is extremely difficult to establish a communication link using
conventional technology due to many impairments typically associated with the
propagation medium and increased signal scattering. Although the challenges for
the design of communication networks, and specifically the Internet of Things
(IoT), in such environments are known, there is no common enabler or solution
for all these applications. Interestingly, the use of RISs in such scenarios
can become such an enabler and a game changer technology. Surprisingly, the
benefits of RIS for wireless networking in underwater and underground medium as
well as in industrial and disaster environments have not been addressed yet. In
this paper, we aim at filling this gap by discussing potential use cases,
deployment strategies and design aspects for RIS devices in underwater IoT,
underground IoT as well as Industry 4.0 and emergency networks. In addition,
novel research challenges to be addressed in this context are described.Comment: 16 pages, 13 figures, submitted for publication in IEEE journa
Coverage Protocols for Wireless Sensor Networks: Review and Future Directions
The coverage problem in wireless sensor networks (WSNs) can be generally
defined as a measure of how effectively a network field is monitored by its
sensor nodes. This problem has attracted a lot of interest over the years and
as a result, many coverage protocols were proposed. In this survey, we first
propose a taxonomy for classifying coverage protocols in WSNs. Then, we
classify the coverage protocols into three categories (i.e. coverage aware
deployment protocols, sleep scheduling protocols for flat networks, and
cluster-based sleep scheduling protocols) based on the network stage where the
coverage is optimized. For each category, relevant protocols are thoroughly
reviewed and classified based on the adopted coverage techniques. Finally, we
discuss open issues (and recommend future directions to resolve them)
associated with the design of realistic coverage protocols. Issues such as
realistic sensing models, realistic energy consumption models, realistic
connectivity models and sensor localization are covered
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