Direction of Arrival Estimation for Nanoscale Sensor Networks

TL;DR

This paper explores the use of the MUSIC algorithm for accurate direction of arrival estimation in nanoscale wireless sensor networks using terahertz pulses, demonstrating high precision with minimal energy.

Contribution

It applies the MUSIC algorithm to NWSNs with terahertz pulses, identifying optimal pulse shapes and demonstrating high-accuracy DOA estimation at nanoscale energy levels.

Findings

Gaussian pulses at 6 THz yield best DOA accuracy

MUSIC achieves less than one degree error at 6 meters distance

Effective with pulse energy as low as 1 atto Joule

Abstract

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.