Pulse-Based Distance Accumulation Localization Algorithm for Wireless Nanosensor Networks | Zendy

Lina Zhou | Zendy; Guangjie Han | Zendy; Li Liu | Zendy

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Pulse-Based Distance Accumulation Localization Algorithm for Wireless Nanosensor Networks

Author(s) -

Lina Zhou,

Guangjie Han,

Li Liu

Publication year - 2017

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2017.2732351

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Wireless nanosensor networks (WNSNs) consist of nano-sized communication devices, which are equipped with nano-transceivers, nano-antennas, and other functional modules. A nanosensor is an integrated device that ranges from 10 to 100 μm² in size. Due to the limited communication capabilities of WNSNs, existing localization algorithms and protocols for wireless sensor networks (WSNs) are no longer applicable to WNSNs. This paper proposes a pulse-based distance accumulation (PBDA) localization algorithm for WNSNs that can be utilized to estimate the distance between nodes with known positions and nodes with unknown positions. The algorithm adopts femtosecond-long pulse for terahertz band communication based on ON-OFF keying (OOK) modulation. A clustering algorithm is first employed to reduce the energy consumption and time delay, then the nano-device analyzes the value of the received pulse based on the OOK modulation and estimates the distance between nodes. MATLAB simulations are implemented to verify the performance of PBDA by comparing it against the flooding-based hop-counting algorithm and cluster based hop-counting algorithm in terms of estimated distance accuracy, energy consumption, and time delay. The trilateral positioning method is also utilized to compare the localization error of PBDA with that of distance vector (DV)-hop. The results show that PBDA is able to support WNSNs with very high density in ranging and locating.

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