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 modulation.
Highlights
In recent years, the number of devices connected to the Internet has rapidly increased
The neurons of a human brain can be compared to nodes, while axons can be compared to links in a network
We assumed that the transmitted data came from analog sensors in the considered systems
Summary
The number of devices connected to the Internet has rapidly increased. The inspiration for the design of new ultra-energy-efficient networks can be the human brain which can be compared to the ultra-dense network. The neurons of a human brain can be compared to nodes, while axons can be compared to links in a network. In [13] the microglia functionality from the human brain is applied in a dense network It was already shown in [14] that the digital system with coding can be more energy efficient for longer links while the uncoded digital system is more energy efficient for shorter links. We consider brain-inspired analog and digital transmission in the context of energy-efficient ultra-dense networks, i.e., consisting of short links with moderate attenuation and distortions.
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