PROJECT TITLE :
Mean Energy Efficiency Maximization in Cognitive Radio Channels With PU Outage Constraint
Energy potency (EE) is very crucial for future green wireless communication systems, significantly for cognitive radio networks (CRNs). But, the EE design for CRNs in quick-fading scenarios has not been absolutely studied. This letter investigates the mean EE maximization downside for the secondary user (SU) within the fading cognitive radio channels consisting of both SUs and primary users (PUs). We adopt PU outage chance constraint to ensure the standard of service (QoS) of PUs and think about both the peak and mean transmit power constraints for SUs. But, this downside is nontrivial since the mean EE is nonconvex and PU outage probability constraint belongs to probability constraints. With the aid of the fractional programming and Lagrangian duality theory, we tend to propose an economical algorithm to derive the optimal power allocation strategy for SU to maximize its mean EE while guaranteeing the QoS of PUs. Simulation results assess the performance of our proposed scheme and show the tradeoff between SUs' mean EE and PU outage likelihood threshold solely in some sure range.
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