Abstract
Energy efficiency (EE) is an important metric for a Cognitive radio network (CRN). We focus on the EE maximization problem in a sensing-based spectrum sharing CRN for delay-sensitive applications. With the aid of one-dimension exhaustive search, fractional programming and Lagrange duality method, two energy-efficient optimal sensing time and power allocation policies are derived with the consideration of Average/Peak transmit power (ATP/PTP) constraints and Average interference power (AIP) constraints, respectively. Simulation results show that the proposed policies can achieve higher EE compared to the conventional spectrum sharing schemes.
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