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Flexible, Brain-Inspired Communication in Massive Wireless Networks

Authors: Bartosz Bossy; Pawel Kryszkiewicz; Hanna Bogucka;

Flexible, Brain-Inspired Communication in Massive Wireless Networks

Abstract

In this paper, a new perspective of using flexible, brain-inspired, analog and digital wireless transmission in massive future networks, is presented. Inspired by the nervous impulses transmission mechanisms in the human brain which is highly energy efficient, we consider flexible, wireless analog and digital transmission on very short distances approached from the energy efficiency point of view. The energy efficiency metric is compared for the available transmission modes, taking the circuit power consumption model into account. In order to compare the considered systems, we assume that the transmitted data comes from analog sensors. In the case of the digital transmission scheme, the decoded data are converted back to analog form at the receiving side. Moreover, different power consumption models from the literature and the digital transmission schemes with different performance are analyzed in order to examine if, for some applications and for some channel conditions, the analog transmission can be the energy-efficient alternative of digital communication. The simulation results show that there exist some cases when the analog or simplified digital communication is more energy efficient than digital transmission with QAM modulation.

Keywords

massive communications, Digital Technology, Chemical technology, Internet of Things, Brain, power consumption, TP1-1185, Signal-To-Noise Ratio, internet of things, Article, analog and digital transmission, Humans, Monte Carlo Method, Wireless Technology, energy efficiency, brain inspiration

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
Green
gold