On Green Cognitive Radio Cellular Networks: Dynamic Spectrum and Operation Management

We study a profit maximization problem related to cognitive radio cellular networks in an environmentally- friendly framework. The objective of the primary network (PN) and secondary network (SN) is to maximize their profits while respecting a certain carbon dioxide (CO2) emissions threshold. In this study, the PN can switch off some of its base stations (BSs) powered by mircogrids, and hence leases the spectrum in the corresponding cells, to reduce its footprint. The corresponding users are roamed to the SN infrastructure. In return, the SN receives a certain roaming cost and its users can freely exploit the spectrum. We study two scenarios in which the profits are either separately or jointly maximized. In the disjoint maximization problem, two low complexity algorithms for PN and SN BS on/off switching are proposed to maximize the profit per CO2 emissions utility and determine the amount of the shared bandwidth. In the joint maximization approach, the low complexity algorithm is based on maximizing the sum of weighted profits per CO2. Selected numerical results illustrate the collaboration performance versus various system parameters. We show that the proposed algorithms achieve performances close to those obtained with the exhaustive search method, and that the roaming price and the renewable energy availability are crucial parameters that control the collaboration of both networks.

On Green Cognitive Radio Cellular Networks: Dynamic Spectrum and Operation Management 2016:1 IEEE Access

Institute of Electrical and Electronics Engineers (IEEE)

IEEE Access


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