A novel scalable model of substrate components for deep n-well (DNW) RF MOSFETs with different number of fingers is presented for the first time. The test structure developed in [1] is employed to directly access the ...A novel scalable model of substrate components for deep n-well (DNW) RF MOSFETs with different number of fingers is presented for the first time. The test structure developed in [1] is employed to directly access the characteristics of the substrate to extract the different substrate components. A methodology is developed to directly extract the parameters for the substrate network from the measured data. By using the measured two-port data of a set of nMOSFETs with different number of fingers, with the DNW in grounded and float configuration, respectively, the parameters of the scalable substrate model are obtained. The method and the substrate model are further verified and validated by matching the measured and simulated output admittances. Excellent agreement up to 40 GHz for configurations in common-source has been achieved.展开更多
The main research objective in wireless sensor networks (WSN) domain is to develop algorithms and protocols to ensure minimal energy consumption with maximum network lifetime. In this paper, we propose a novel design ...The main research objective in wireless sensor networks (WSN) domain is to develop algorithms and protocols to ensure minimal energy consumption with maximum network lifetime. In this paper, we propose a novel design for energy harvesting sensor node and cross-layered MAC protocol using three adjacent layers (Physical, MAC and Network) to economize energy for WSN. The basic idea behind our protocol is to re-energize the neighboring nodes using the radio frequency (RF) energy transmitted by the active nodes. This can be achieved by designing new energy harvesting sensor node and redesigning the MAC protocol. The results show that the proposed cross layer CL_EHSN improves the life time of the WSN by 40%.展开更多
文摘A novel scalable model of substrate components for deep n-well (DNW) RF MOSFETs with different number of fingers is presented for the first time. The test structure developed in [1] is employed to directly access the characteristics of the substrate to extract the different substrate components. A methodology is developed to directly extract the parameters for the substrate network from the measured data. By using the measured two-port data of a set of nMOSFETs with different number of fingers, with the DNW in grounded and float configuration, respectively, the parameters of the scalable substrate model are obtained. The method and the substrate model are further verified and validated by matching the measured and simulated output admittances. Excellent agreement up to 40 GHz for configurations in common-source has been achieved.
文摘The main research objective in wireless sensor networks (WSN) domain is to develop algorithms and protocols to ensure minimal energy consumption with maximum network lifetime. In this paper, we propose a novel design for energy harvesting sensor node and cross-layered MAC protocol using three adjacent layers (Physical, MAC and Network) to economize energy for WSN. The basic idea behind our protocol is to re-energize the neighboring nodes using the radio frequency (RF) energy transmitted by the active nodes. This can be achieved by designing new energy harvesting sensor node and redesigning the MAC protocol. The results show that the proposed cross layer CL_EHSN improves the life time of the WSN by 40%.
