Flexible, Brain-Inspired Communication in Massive Wireless Networks

Sensors (Basel). 2020 Mar 12;20(6):1587. doi: 10.3390/s20061587.

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: Internet of Things; analog and digital transmission; brain inspiration; energy efficiency; massive communications; power consumption.

MeSH terms

  • Brain / physiology*
  • Digital Technology / methods*
  • Humans
  • Internet of Things
  • Monte Carlo Method
  • Signal-To-Noise Ratio
  • Wireless Technology*