577 research outputs found
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
Wireless sensor networks monitor dynamic environments that change rapidly
over time. This dynamic behavior is either caused by external factors or
initiated by the system designers themselves. To adapt to such conditions,
sensor networks often adopt machine learning techniques to eliminate the need
for unnecessary redesign. Machine learning also inspires many practical
solutions that maximize resource utilization and prolong the lifespan of the
network. In this paper, we present an extensive literature review over the
period 2002-2013 of machine learning methods that were used to address common
issues in wireless sensor networks (WSNs). The advantages and disadvantages of
each proposed algorithm are evaluated against the corresponding problem. We
also provide a comparative guide to aid WSN designers in developing suitable
machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial
Max-min Fair Wireless Energy Transfer for Secure Multiuser Communication Systems
This paper considers max-min fairness for wireless energy transfer in a
downlink multiuser communication system. Our resource allocation design
maximizes the minimum harvested energy among multiple multiple-antenna energy
harvesting receivers (potential eavesdroppers) while providing quality of
service (QoS) for secure communication to multiple single-antenna information
receivers. In particular, the algorithm design is formulated as a non-convex
optimization problem which takes into account a minimum required
signal-to-interference-plus-noise ratio (SINR) constraint at the information
receivers and a constraint on the maximum tolerable channel capacity achieved
by the energy harvesting receivers for a given transmit power budget. The
proposed problem formulation exploits the dual use of artificial noise
generation for facilitating efficient wireless energy transfer and secure
communication. A semidefinite programming (SDP) relaxation approach is
exploited to obtain a global optimal solution of the considered problem.
Simulation results demonstrate the significant performance gain in harvested
energy that is achieved by the proposed optimal scheme compared to two simple
baseline schemes.Comment: 5 pages, invited paper, IEEE Information Theory Workshop 2014,
Hobart, Tasmania, Australia, Nov. 201
- …