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The deployment of relay stations (RSs) offers a promising and viable approach to satisfy the increasing need of high data rate in cellular networks. With the expected increase of the number of RSs, the energy efficiency (EE) becomes a crucial system design parameter. One of the most effective energy saving methods is to switch off some stations. In this paper, joint base station (BS) and RS sleep...
In this paper, a reinforcement learning-based sleep scheduling for coverage (RLSSC) algorithm is proposed for sustainable time-slotted operation in rechargeable sensor networks. RLSSC is a two-stage sleep scheduling algorithm. It includes the precedence operator-based group formation algorithm and the Q learning-based active node selection algorithm. First, a precedence operator is designed in the...
In this paper, a joint Base Station (BS) and Relay Station (RS) sleep scheduling algorithm is proposed for relay-aided cellular networks based on Cellular Automata (CA). By applying the self-organizing character of CA, the number of active BSs and RSs converges to a stable state to save energy. A suboptimal value of energy efficiency of the relay-aided cellular network is obtained via a CA algorithm...
Energy harvesting sensor networks sparked extensive research interest in recent years. However, little attention has been paid to sleep scheduling for area surveillance in rechargeable sensor networks. In this paper, we attempt to settle the problem of keeping rechargeable Wireless Sensor Networks operating for a long time while satisfying certain desired area coverage and energy consumption balance...
Target tracking is a typical application in wireless sensor networks. Many target tracking algorithms have been proposed. However, the limited energy storage of sensors affect the performance of target tracking. The emerging energy harvesting technology can alleviate the energy limitation problem. At present, few work on target tracking in energy harvesting sensor networks has been done. In this paper,...
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