Direction of Arrival Estimation for Nanoscale Sensor Networks

• Main Authors: Prasad, Shree M., Panigrahi, Trilochan, Hassan, Mahbub
• Format: Text
• Language: unknown
• Published: arXiv 2018
• Subjects: Emerging Technologies cs.ET; Signal Processing eess.SP; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Iceland
• Online Access: https://dx.doi.org/10.48550/arxiv.1807.04435; https://arxiv.org/abs/1807.04435

Nanoscale wireless sensor networks (NWSNs) could be within reach soon using graphene-based antennas, which resonate in 0.1-10 terahertz band. To conserve the limited energy available at nanoscale, it is expected that NWSNs will communicate using extremely short pulses on the order of femtoseconds. Accurate estimation of direction of arrival (DOA) for such terahertz pulses will help realize many useful applications for NWSNs. In this paper, using the well-known MUltiple SIgnal Classification (MUSIC) algorithm, we study DOA estimation for NWSNs for different energy levels, distances, pulse shapes, and frequencies. Our analyses reveal that the best DOA estimation is achieved with the first order Gaussian pulses, which emit their peak energy at 6 THz. Based on Monte Carlo simulations, we demonstrate that MUSIC algorithm is capable of estimating DOA with root mean square error less than one degree from a distance of around 6 meter for pulse energy as little as 1 atto Joule. : 6 Pages, 9 figures, Camera Ready Version, NANOCOM '18: ACM The Fifth Annual International Conference on Nanoscale Computing and Communication, September 5--7, 2018, Reykjavik, Iceland