Dynamic power management （DPM） in wireless sensor nodes is a well-known technique for reducing idle energy consumption. DPM controls a node＇s operating mode by dynamically toggling the on/off status of its units ba...Dynamic power management （DPM） in wireless sensor nodes is a well-known technique for reducing idle energy consumption. DPM controls a node＇s operating mode by dynamically toggling the on/off status of its units based on predictions of event occurrences. However, since each mode change induces some overhead in its own right, guaranteeing DPM＇s eificiency is no mean feat in environments exhibiting non-determinism and uncertainty with unknown statistics. Our solution suite in this paper, collectively referred to as cognitive power management （CPM）, is a principled attempt toward enabling DPM in statistically unknown settings and gives two different analytical guarantees. Our first design is based on learning automata and guarantees better-than-pure-chance DPM in the face of non-stationary event processes. Our second solution caters tor an even more general setting in which event occurrences may take on an adversarial character. In this case, we formulate the interaction of an individual mote with its environment in terms of a repeated zero-sum game in which the node relies on a no-external-regret procedure to learn its mini-max strategies in an online fashion. We conduct numerical experiments to measure the performance of our schemes in terms of network lifetime and event loss percentage.展开更多
In order to improve the Energy Efficiency(EE)and spectrum utilization of Cognitive Wireless Powered Networks(CWPNs),a combined spatial-temporal Energy Harvesting(EH)and relay selection scheme is proposed.In the propos...In order to improve the Energy Efficiency(EE)and spectrum utilization of Cognitive Wireless Powered Networks(CWPNs),a combined spatial-temporal Energy Harvesting(EH)and relay selection scheme is proposed.In the proposed scheme,for protecting the Primary User(PU),a two-layer guard zone is set outside the PU based on the outage probability threshold of the PU.Moreover,to increase the energy of the CWPNs,the EH zone in the two-layer guard zone allows the Secondary Users(SUs)to spatially harvest energy from the Radio Frequency(RF)signals of temporally active PUs.To improve the utilization of the PU spectrum,the guard zone outside the EH zone allows for the constrained power transmission of SUs.Moreover,the relay selection transmission is designed in the transmission zone of the SU to improve the EE of the CWPNs.In addition to the EE of the CWPNs,the outage probabilities of the SU and PU are derived.The results reveal that the setting of a two-layer guard zone can effectively reduce the outage probability of the PU and improve the EE of CWPNs.Furthermore,the relay selection transmission decreases the outage probabilities of the SUs.展开更多
文摘Dynamic power management （DPM） in wireless sensor nodes is a well-known technique for reducing idle energy consumption. DPM controls a node＇s operating mode by dynamically toggling the on/off status of its units based on predictions of event occurrences. However, since each mode change induces some overhead in its own right, guaranteeing DPM＇s eificiency is no mean feat in environments exhibiting non-determinism and uncertainty with unknown statistics. Our solution suite in this paper, collectively referred to as cognitive power management （CPM）, is a principled attempt toward enabling DPM in statistically unknown settings and gives two different analytical guarantees. Our first design is based on learning automata and guarantees better-than-pure-chance DPM in the face of non-stationary event processes. Our second solution caters tor an even more general setting in which event occurrences may take on an adversarial character. In this case, we formulate the interaction of an individual mote with its environment in terms of a repeated zero-sum game in which the node relies on a no-external-regret procedure to learn its mini-max strategies in an online fashion. We conduct numerical experiments to measure the performance of our schemes in terms of network lifetime and event loss percentage.
文摘In order to improve the Energy Efficiency(EE)and spectrum utilization of Cognitive Wireless Powered Networks(CWPNs),a combined spatial-temporal Energy Harvesting(EH)and relay selection scheme is proposed.In the proposed scheme,for protecting the Primary User(PU),a two-layer guard zone is set outside the PU based on the outage probability threshold of the PU.Moreover,to increase the energy of the CWPNs,the EH zone in the two-layer guard zone allows the Secondary Users(SUs)to spatially harvest energy from the Radio Frequency(RF)signals of temporally active PUs.To improve the utilization of the PU spectrum,the guard zone outside the EH zone allows for the constrained power transmission of SUs.Moreover,the relay selection transmission is designed in the transmission zone of the SU to improve the EE of the CWPNs.In addition to the EE of the CWPNs,the outage probabilities of the SU and PU are derived.The results reveal that the setting of a two-layer guard zone can effectively reduce the outage probability of the PU and improve the EE of CWPNs.Furthermore,the relay selection transmission decreases the outage probabilities of the SUs.
