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Non-Orthogonal Multiple Access for Ubiquitous Wireless Sensor Networks

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Authors

Anwar, Asim

Seet, Boon-Chong

Ding, Zhiguo

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MDPI AG

Abstract

Ubiquitous wireless sensor networks (UWSNs) have become a critical technology for enabling smart cities and other ubiquitous monitoring applications. Their deployment, however, can be seriously hampered by the spectrum available to the sheer number of sensors for communication. To support the communication needs of UWSNs without requiring more spectrum resources, the power-domain non-orthogonal multiple access (NOMA) technique originally proposed for 5th Generation (5G) cellular networks is investigated for UWSNs for the first time in this paper. However, unlike 5G networks that operate in the licensed spectrum, UWSNs mostly operate in unlicensed spectrum where sensors also experience cross-technology interferences from other devices sharing the same spectrum. In this paper, we model the interferences from various sources at the sensors using stochastic geometry framework. To evaluate the performance, we derive a theorem and present new closed form expression for the outage probability of the sensors in a downlink scenario under interference limited environment. In addition, diversity analysis for the ordered NOMA users is performed. Based on the derived outage probability, we evaluate the average link throughput and energy consumption efficiency of NOMA against conventional orthogonal multiple access (OMA) technique in UWSNs. Further, the required computational complexity for the NOMA users is presented.

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cross-technology interference, non-orthogonal multiple access, stochastic geometry, ubiquitous wireless sensor networks, unlicensed spectrum, 4613 Theory Of Computation, 40 Engineering, 46 Information and Computing Sciences, 4006 Communications Engineering, 4605 Data Management and Data Science, 4606 Distributed Computing and Systems Software, 7 Affordable and Clean Energy, 0301 Analytical Chemistry, 0805 Distributed Computing, 0906 Electrical and Electronic Engineering, Analytical Chemistry, 4008 Electrical engineering, 4009 Electronics, sensors and digital hardware, 4104 Environmental management, 4606 Distributed computing and systems software

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Sensors, ISSN: 1424-2818 (Print); 1424-8220 (Online), MDPI AG, 18(2), E516-. doi: 10.3390/s18020516

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© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article

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Except where otherwise noted, this item's license is described as Creative Commons Attribution (CC BY) license