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On Green Energy Powered Cognitive Radio Networks (1405.5747v2)

Published 22 May 2014 in cs.NI

Abstract: Green energy powered cognitive radio (CR) network is capable of liberating the wireless access networks from spectral and energy constraints. The limitation of the spectrum is alleviated by exploiting cognitive networking in which wireless nodes sense and utilize the spare spectrum for data communications, while dependence on the traditional unsustainable energy is assuaged by adopting energy harvesting (EH) through which green energy can be harnessed to power wireless networks. Green energy powered CR increases the network availability and thus extends emerging network applications. Designing green CR networks is challenging. It requires not only the optimization of dynamic spectrum access but also the optimal utilization of green energy. This paper surveys the energy efficient cognitive radio techniques and the optimization of green energy powered wireless networks. Existing works on energy aware spectrum sensing, management, and sharing are investigated in detail. The state of the art of the energy efficient CR based wireless access network is discussed in various aspects such as relay and cooperative radio and small cells. Envisioning green energy as an important energy resource in the future, network performance highly depends on the dynamics of the available spectrum and green energy. As compared with the traditional energy source, the arrival rate of green energy, which highly depends on the environment of the energy harvesters, is rather random and intermittent. To optimize and adapt the usage of green energy according to the opportunistic spectrum availability, we discuss research challenges in designing cognitive radio networks which are powered by energy harvesters.

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Authors (3)
  1. Xueqing Huang (8 papers)
  2. Tao Han (233 papers)
  3. Nirwan Ansari (43 papers)
Citations (201)

Summary

  • The paper introduces innovative energy harvesting techniques to power CR networks, enhancing spectrum efficiency while reducing energy consumption.
  • The study categorizes power-aware strategies, cooperative designs, and green resource optimization to maximize system performance.
  • The research highlights practical benefits for rural and smart grid deployments through adaptive, decentralized energy management solutions.

Overview of Green Energy Powered Cognitive Radio Networks

The paper "On Green Energy Powered Cognitive Radio Networks" examines the integration of green energy solutions with cognitive radio (CR) networks. It investigates the use of energy harvesting (EH) technologies to power CR networks, which aim to address both the spectrum inefficiency and energy sustainability challenges prevalent in modern wireless communication systems.

Key Contributions and Findings

The authors provide a comprehensive survey on energy-efficient cognitive radio systems and delve into the optimization of green energy utilization within wireless networks. They discuss the challenges and potential of embedding energy harvesting technologies in CR networks to capitalize on underutilized spectral resources while reducing reliance on nonrenewable energy sources.

The paper categorizes the state-of-the-art energy-efficient cognitive radio systems into three main aspects:

  1. Power-aware Cognitive Functionality: This encompasses energy minimization, performance maximization, and utility maximization strategies. It highlights the trade-offs between these strategies in terms of energy consumption and system performance benchmarks like 'bit/Joule'.
  2. Design of Energy-efficient Wireless Access Systems: The analysis includes cooperative communications, such as relay and cooperative CR, and explores the advantages of emerging LTE-Advanced networks implementing cognitive small cells.
  3. Optimization of Green Cognitive Radio Networks: The focus here is on how green energy resources can be effectively utilized through cognitive functionalities. The paper outlines the dynamic and opportunistic nature of spectrum availability and energy harvesting, requiring sophisticated design solutions for robustness and adaptability.

Numerical Results and Claims

The paper examines various resource allocation and optimization techniques, observing the need for both centralized and decentralized strategies to maximize energy efficiency while maintaining adequate quality of service (QoS). Considering different energy harvesting models and RF energy harvesting mechanisms, solutions are proposed to seamlessly integrate these technologies into existing CR frameworks. The utility-based perspectives demonstrate the potential for significant energy savings and operational feasibility, even when traditional grid energy resources are intermittent or absent.

Implications and Future Directions

The integration of green energy with CR networks has significant implications for the sustainability of wireless infrastructure. From the perspective of environmental and economic sustainability, energy-efficient CR networks using green power resources can dramatically reduce both carbon footprints and operational costs. This carries over to practical applications, such as rural area network deployments where grid power is scarce, and hybrid-powered structures deeply interconnected with smart grid architectures.

Considering future developments, emphasis needs to be placed on real-time energy management algorithms, improving the accuracy of opportunistic spectrum sensing, and enabling seamless multi-user access coordination in heterogeneous CR networks. The challenges of dynamically fluctuating energy arrivals and spectrum access constraints underscore the necessity for innovative adaptive and scalable solutions.

In conclusion, enabling green energy powered cognitive radio networks requires a holistic approach that balances technical optimization with strategic deployment aligning with environmental and economic goals. This paper paves the way for academics and practitioners to further explore and develop these next-generation sustainable communication systems.