返回Google圖書搜尋

Reliable Communication in Distributed Sensor Networks

出版	Universitätsbibliothek, 2019
URL	http://books.google.com.hk/books?id=ZmwQyAEACAAJ&hl=&source=gbs_api

註釋Sensor networks have gained considerable attention in the past due to their self-organized operation. In this PhD thesis, we target those heterogeneous sensor networks in which backbone (or ground) nodes establish a core network to deliver data to a sink, whereas mobile nodes transmit both localization and encounter information to this backbone network. In the case of errors, the transmitted information is lost and thus needs to be retransmitted. Considering extremely energy-constrained nodes (having weight of less than 2 g), such retransmissions are quite expensive. Hence, we focus on improving the energy-efficiency and communication reliability in such ultra-low power sensor networks. We begin this thesis by investigating the potential of using a square sub-carrier modulation alongside Binary Phase-Shift Keying (BPSK) to transmit localization and data information simultaneously at a single carrier. To assess the performance in both simulations and practical experiments, we develop the whole system in a Software Defined Radio (SDR)-based platform. Our results show that the sub-carrier modulation performs only marginally worse than the BPSK, however, using both of them together saves energy at the mobile node. We then turn our attention towards improved communication reliability. For that, we exploit the distributed nature of the ground network and use it as a distributed antenna array to apply diversity combining. In order to employ receive diversity efficiently, we propose the concept of selective sample forwarding. We build upon our SDR-based implementation and experimentally show that the proposed approach improves the Packet Delivery Rate (PDR) by more than 10 % in comparison to not using diversity combining at all. Finally, we address the cost of forwarding the received information through the ground network to a central sink, where diversity combining is ... ; eng