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Green energy harvesting protocols for intelligent wireless communication systems

Green energy harvesting protocols for intelligent wireless communication systems

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With the exponential growth of economical and sophisticated user devices in the digitized world, the competence of communicating high volume of data such as high-definition videos or high-quality multimedia has become users' requirements nowadays. However, spectral-efficient networking for high-speed data and self-sustainability in energy are two major trade-offs in design of energy-aware next-generation wireless communications. Efficient utilization of energy resources reduces the cost of power consumption that can improve the economic characteristics of the network. In this chapter, we investigate the energy and quality-ofservice (QoS) aware smart services using artificial intelligence (AI) assisted automated wireless communications, describes the novel energy state prediction model, online optimization algorithms for energy-harvesting (EH), and enhancement of autonomy by maximizing the throughput based on self-sustainability. The intelligent power management technological developments while satisfying the desired QoS paving the way for AI-powered mechanisms in future wireless networking applications.

Chapter Contents:

  • 3.1 Background and motivation
  • 3.2 Architecture of energy harvesting wireless networks
  • 3.3 Energy harvesting models for intelligent wireless communications
  • 3.3.1 Solar energy predication model
  • 3.3.1.1 Exponentially weighted moving average
  • 3.3.1.2 Modified EWMA
  • 3.3.1.3 Weather conditioned moving average
  • 3.3.1.4 Proenergy prediction model
  • 3.3.1.5 QL-SEP algorithm
  • 3.3.2 RF energy prediction model
  • 3.4 AI-assisted online algorithms for optimal energy harvesting communications
  • 3.4.1 Offline policies
  • 3.4.2 Online policies
  • 3.5 Optimal resource allocation in EH self-sustainable communication systems
  • 3.5.1 Self-sustainable D2D communication
  • 3.5.2 MIMO simultaneous wireless information and power transfer (SWIPT)
  • 3.5.3 Resource allocation in distinct EH wireless networks
  • 3.6 Conclusion and future directions
  • References

Inspec keywords: telecommunication computing; telecommunication power management; optimisation; artificial intelligence; energy harvesting; quality of service; protocols; radio networks

Other keywords: AI-powered mechanisms; economical user devices; high-speed data; exponential growth; future wireless networking applications; wireless communications; self-sustainability; high-definition videos; energy-aware next-generation; economic characteristics; energy-harvesting; GreenGreenGreen energy harvesting protocols; energy state prediction model; high-quality multimedia; power consumption; intelligent wireless communication systems; spectral-efficient networking; digitized world; energy resources; intelligent power management technological developments; artificial intelligence

Subjects: Optimisation techniques; Optimisation techniques; Protocols; Energy harvesting; Mobile radio systems; Protocols; Communications computing; Energy harvesting; Radio links and equipment

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