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RF energy harvesting is a promising potential solution to provide convenient and perpetual energy supplies to low-power wireless sensor networks. In this paper, we investigate the energy harvesting performance of a wireless sensor node powered by harvesting RF energy from an existing multiple-antenna transmitter. Specifically, we propose a random unitary beamforming (RUB) based cooperative beam selection...
RF energy harvesting is a promising potential solution for providing convenient and perpetual energy supply to low-power wireless sensor networks. In this paper, we investigate the performance of overlaid wireless sensor transmission powered by RF energy harvesting from existing wireless system. Specifically, we derive the exact closed-form expression for the distribution function of harvested energy...
Traditional clustering algorithms for WSN (wireless sensor networks) select only one CH (cluster head) in each cluster, which consumes energy at the CH fast and shortens the network lifetime greatly. In this paper, EBCMS (energy-balanced clustering algorithm with master/slave method) is proposed to solve this problem. The key idea of the algorithm is that one master CH and two slave CHs are chosen...
In this paper, we consider cooperative spectrum sensing in OFDM based on energy detection in MIMO cognitive radio sensor networks. Soft combination of the observed energy values from different cognitive radio users is investigated. Square-law-combining (SLC) is theoretically proved to be nearly optimal in low signal-to-noise ratio (SNR) region, an usual scenario in the context of MIMO cognitive radio...
Majority of evaluation methods on interference temperature algorithms are based on the assumption that either the interference signals or the user's signals are no directions. This is a mathematical constraint that is not satisfied in many applications. In fact, without consideration the signal directions increase estimation interference temperature, that is, reduce the frequency utilizing chance...
DMAC using the staggered wakeup schedule can achieve both low latency and low energy consumption. However, the data gathering tree built by DMAC is fixed permanently. A fixed data gathering tree can't adapt to the variability in the environment of wireless sensor networks, and it needs to be reconstructed frequently to suit the current environment. For example, the interference is a factor that will...
In this work we consider lifetime-aware resource management for sensor network using distributed genetic algorithm (GA). Our goal is to allocate different detection methods to different sensor nodes in the way such that the required detection probability can be achieved while the network lifetime is maximized. The contribution of this paper is twofold. Firstly, the resource management problem is formulated...
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